{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from lxml.html import fromstring\n",
    "import time\n",
    "from random import random\n",
    "from requests_html import HTMLSession"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from selenium import webdriver\n",
    "from selenium.webdriver.common.desired_capabilities import DesiredCapabilities\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:7: DeprecationWarning: use options instead of chrome_options\n",
      "  import sys\n"
     ]
    }
   ],
   "source": [
    "opts = webdriver.ChromeOptions()\n",
    "opts.add_argument('--no-sandbox')\n",
    "opts.add_argument('window-size=1920x3000') \n",
    "opts.add_argument('--disable-gpu') \n",
    "opts.add_argument('--hide-scrollbars') \n",
    "\n",
    "driver = webdriver.Chrome( chrome_options = opts) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "driver.get(\"https://www.cnki.net/\")\n",
    "# 打开知网"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'中山大学南方学院'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "driver.find_element_by_id(\"Ecp_loginShowName1\").get_attribute('innerHTML')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "element=driver.find_element_by_id('highSearch')\n",
    "element.get_attribute('innerHTML')\n",
    "element.click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'CDwindow-E5D62715DB50D077576616163872F857'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "driver.current_window_handle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['CDwindow-E5D62715DB50D077576616163872F857',\n",
       " 'CDwindow-C740F2A5AAA6912822728B3AE692D3C8']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "driver.window_handles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: DeprecationWarning: use driver.switch_to.window instead\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "driver.switch_to_window(driver.window_handles[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "element=driver.find_element_by_xpath('/html/body/div[3]/div[1]/div/ul[1]/li[1]/a/span')\n",
    "element.get_attribute('innerHTML')\n",
    "element.click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "element=driver.find_element_by_xpath('/html/body/div[2]/div/div[2]/ul/li[4]')\n",
    "element.click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "element=driver.find_element_by_xpath('/html/body/div[2]/div/div[2]/div/div[1]/div[1]/div[2]/textarea')\n",
    "element.clear()\n",
    "element.send_keys(' SU=“大数据” AND SU=“人工智能”')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "element=driver.find_element_by_xpath('/html/body/div[2]/div/div[2]/div/div[1]/div[1]/div[2]/div[2]/input')\n",
    "element.click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'928'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "driver.find_element_by_xpath('//*[@id=\"countPageDiv\"]/span[1]/em').get_attribute('innerHTML')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "element=driver.find_element_by_xpath('//*[@id=\"perPageDiv\"]/div/i')\n",
    "element.click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "element=driver.find_element_by_xpath('//*[@id=\"perPageDiv\"]/ul/li[3]/a')\n",
    "element.click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>篇名</th>\n",
       "      <th>作者</th>\n",
       "      <th>刊名</th>\n",
       "      <th>发表时间</th>\n",
       "      <th>被引</th>\n",
       "      <th>下载</th>\n",
       "      <th>操作</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>基于大数据和人工智能技术的智库媒体转型——以南方都市报为例</td>\n",
       "      <td>郭全中</td>\n",
       "      <td>新闻与写作</td>\n",
       "      <td>2021-06-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>厂商运用大数据和人工智能的经济学分析</td>\n",
       "      <td>何大安</td>\n",
       "      <td>上海师范大学学报(哲学社会科学版)</td>\n",
       "      <td>2021-05-25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>249.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>人工智能和大数据中的伦理与隐私</td>\n",
       "      <td>丁磊</td>\n",
       "      <td>电子技术</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>618.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>大数据背景下地方高校人工智能方向人才培养模式探索</td>\n",
       "      <td>叶青; 刘长华</td>\n",
       "      <td>湖北工程学院学报</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>人工智能及大数据的网络安全态势感知研究</td>\n",
       "      <td>王晓娜; 李晓宇; 李芙蓉</td>\n",
       "      <td>网络安全技术与应用</td>\n",
       "      <td>2021-05-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>373.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>大数据、人工智能和实体经济深度融合运用探析</td>\n",
       "      <td>孟宪坤</td>\n",
       "      <td>中小企业管理与科技(中旬刊)</td>\n",
       "      <td>2021-05-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>170.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>大数据+人工智能 构建教育大数据新产业</td>\n",
       "      <td>田雪松</td>\n",
       "      <td>软件和集成电路</td>\n",
       "      <td>2021-05-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>85.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>大数据时代人工智能在计算机网络技术中的应用研究</td>\n",
       "      <td>郁陶</td>\n",
       "      <td>电子世界</td>\n",
       "      <td>2021-05-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>65.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>基于大数据时代人工智能在计算机网络技术中的应用</td>\n",
       "      <td>李晓霞</td>\n",
       "      <td>电子测试</td>\n",
       "      <td>2021-05-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>大数据时代人工智能技术在农业领域的研究进展</td>\n",
       "      <td>朱志锋</td>\n",
       "      <td>新农业</td>\n",
       "      <td>2021-05-10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>221.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>大数据时代人工智能与学前教育的融合路径</td>\n",
       "      <td>高文慧</td>\n",
       "      <td>中阿科技论坛(中英文)</td>\n",
       "      <td>2021-05-10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>大数据与人工智能环境下“一主三辅”情报研究工作模式  网络首发</td>\n",
       "      <td>梁春华</td>\n",
       "      <td>情报理论与实践</td>\n",
       "      <td>2021-05-08 11:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>187.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>13</td>\n",
       "      <td>后疫情时代教育创新发展的新视域与中国卓越探索——出席“2020全球人工智能与教育大数据大会”的思考</td>\n",
       "      <td>陈丽; 任萍萍; 张文梅</td>\n",
       "      <td>中国电化教育</td>\n",
       "      <td>2021-05-08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>961.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>大数据时代下人工智能在计算机网络技术中的运用探讨</td>\n",
       "      <td>杨文学</td>\n",
       "      <td>电脑知识与技术</td>\n",
       "      <td>2021-05-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "      <td>大数据时代背景下人工智能在侦查中的应用思考</td>\n",
       "      <td>何明; 李丽; 任红春</td>\n",
       "      <td>电子技术与软件工程</td>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>关于大数据技术在人工智能中应用的探讨</td>\n",
       "      <td>王瑛</td>\n",
       "      <td>现代工业经济和信息化</td>\n",
       "      <td>2021-04-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>138.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>大数据背景下人工智能在智慧交通中的应用研究</td>\n",
       "      <td>王洪斌</td>\n",
       "      <td>电脑知识与技术</td>\n",
       "      <td>2021-04-25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>658.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>18</td>\n",
       "      <td>大数据时代背景下人工智能在计算机网络技术中的应用探索</td>\n",
       "      <td>戚引松</td>\n",
       "      <td>科技与创新</td>\n",
       "      <td>2021-04-25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>371.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>19</td>\n",
       "      <td>大数据时代人工智能在计算机网络技术中的应用</td>\n",
       "      <td>李殿涛</td>\n",
       "      <td>内江科技</td>\n",
       "      <td>2021-04-25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>533.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>20</td>\n",
       "      <td>大数据与人工智能技术助力社区应急管理</td>\n",
       "      <td>王惠明; 黄焯威; 付一多</td>\n",
       "      <td>中国物业管理</td>\n",
       "      <td>2021-04-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>89.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>21</td>\n",
       "      <td>人工智能和大数据对会计学科发展的影响</td>\n",
       "      <td>丁金川</td>\n",
       "      <td>纳税</td>\n",
       "      <td>2021-04-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>大数据时代人工智能审计模式研究</td>\n",
       "      <td>杨亦颖</td>\n",
       "      <td>新会计</td>\n",
       "      <td>2021-04-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>73.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>23</td>\n",
       "      <td>人工智能在会计管理中的应用——评《大数据背景下智能会计信息系统构建与应用》</td>\n",
       "      <td>王巍</td>\n",
       "      <td>中国科技论文</td>\n",
       "      <td>2021-04-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>24</td>\n",
       "      <td>大数据下人工智能计算机网络技术中的发展探究</td>\n",
       "      <td>郭福燕; 黄稳稳</td>\n",
       "      <td>网络安全技术与应用</td>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>350.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>25</td>\n",
       "      <td>大数据在人工智能中的应用</td>\n",
       "      <td>龚方生</td>\n",
       "      <td>计算机与网络</td>\n",
       "      <td>2021-04-12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>大数据和人工智能在新闻传播生产模式中的应用</td>\n",
       "      <td>姜晓斐</td>\n",
       "      <td>传媒论坛</td>\n",
       "      <td>2021-04-08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>252.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26</td>\n",
       "      <td>27</td>\n",
       "      <td>数学地球科学跨越发展的十年：大数据、人工智能算法正在改变地质学</td>\n",
       "      <td>周永章;左仁广;刘刚;袁峰;毛先成</td>\n",
       "      <td>矿物岩石地球化学通报</td>\n",
       "      <td>2021-04-07 11:49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>344.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27</td>\n",
       "      <td>28</td>\n",
       "      <td>疫情下大数据与人工智能技术在教育领域的应用与思考</td>\n",
       "      <td>王桂平; 张涵</td>\n",
       "      <td>计算机时代</td>\n",
       "      <td>2021-04-07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>基于“人工智能+大数据”智慧校园整体规划和建设</td>\n",
       "      <td>任新华; 王文冀; 张学燕</td>\n",
       "      <td>电脑知识与技术</td>\n",
       "      <td>2021-04-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>大数据网络安全防御中人工智能技术的运用</td>\n",
       "      <td>张超; 郑茗泽</td>\n",
       "      <td>中国新通信</td>\n",
       "      <td>2021-04-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30</td>\n",
       "      <td>31</td>\n",
       "      <td>物联网大数据人工智能时代引领物业管理新思潮</td>\n",
       "      <td>陶青</td>\n",
       "      <td>中国中小企业</td>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>97.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31</td>\n",
       "      <td>32</td>\n",
       "      <td>大数据时代人工智能在计算机网络技术中的应用研究</td>\n",
       "      <td>雷学智</td>\n",
       "      <td>信息记录材料</td>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>32</td>\n",
       "      <td>33</td>\n",
       "      <td>大数据时代人工智能在计算机网络技术中的应用</td>\n",
       "      <td>杨彦青; 郭献崇</td>\n",
       "      <td>科技风</td>\n",
       "      <td>2021-03-29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>33</td>\n",
       "      <td>34</td>\n",
       "      <td>大数据背景下人工智能在计算机网络技术中的应用研究</td>\n",
       "      <td>段冬; 张娴</td>\n",
       "      <td>电脑知识与技术</td>\n",
       "      <td>2021-03-25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>101.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>34</td>\n",
       "      <td>35</td>\n",
       "      <td>大数据技术在人工智能的运用</td>\n",
       "      <td>李斌</td>\n",
       "      <td>智能建筑与智慧城市</td>\n",
       "      <td>2021-03-25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>339.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>35</td>\n",
       "      <td>36</td>\n",
       "      <td>基于大数据应用和人工智能决策的电网辅助控制体系探讨</td>\n",
       "      <td>蔡新雷; 齐颖</td>\n",
       "      <td>电工技术</td>\n",
       "      <td>2021-03-25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>36</td>\n",
       "      <td>37</td>\n",
       "      <td>基于人工智能的网络舆情大数据传播特征挖掘系统</td>\n",
       "      <td>洪晓艺</td>\n",
       "      <td>电子技术</td>\n",
       "      <td>2021-03-20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>37</td>\n",
       "      <td>38</td>\n",
       "      <td>一种人工智能精细识别城市用地的方法探索——基于建筑形态与业态大数据</td>\n",
       "      <td>杨俊宴; 邵典; 王桥; 张宇豪</td>\n",
       "      <td>城市规划</td>\n",
       "      <td>2021-03-15 17:20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>321.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>38</td>\n",
       "      <td>39</td>\n",
       "      <td>大数据与人工智能时代电子发票的内部控制研究</td>\n",
       "      <td>王佳</td>\n",
       "      <td>纳税</td>\n",
       "      <td>2021-03-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>175.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39</td>\n",
       "      <td>40</td>\n",
       "      <td>大数据时代人工智能在计算机网络技术中的应用</td>\n",
       "      <td>韩玲玲</td>\n",
       "      <td>电子世界</td>\n",
       "      <td>2021-03-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>144.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>40</td>\n",
       "      <td>41</td>\n",
       "      <td>大数据+人工智能推动市域治理模式变革</td>\n",
       "      <td>郑宇</td>\n",
       "      <td>法人</td>\n",
       "      <td>2021-03-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>41</td>\n",
       "      <td>42</td>\n",
       "      <td>人工智能与大数据在食品安全信息监管中的应用</td>\n",
       "      <td>张成梅; 王雅洁; 陶衡; 郝淼; 杨鑫</td>\n",
       "      <td>电子技术与软件工程</td>\n",
       "      <td>2021-03-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>58.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>42</td>\n",
       "      <td>43</td>\n",
       "      <td>大数据与人工智能创新实验室</td>\n",
       "      <td>NaN</td>\n",
       "      <td>太原学院学报(自然科学版)</td>\n",
       "      <td>2021-03-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>43</td>\n",
       "      <td>44</td>\n",
       "      <td>基于大数据和人工智能进行网络舆情分析的研究</td>\n",
       "      <td>郭乐江; 肖蕾; 何松; 胡俊</td>\n",
       "      <td>长江信息通信</td>\n",
       "      <td>2021-03-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>118.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>44</td>\n",
       "      <td>45</td>\n",
       "      <td>大数据/人工智能背景下IT专业基于R的概率论与数理统计教学改革</td>\n",
       "      <td>汪浩; 李莹</td>\n",
       "      <td>计算机教育</td>\n",
       "      <td>2021-03-10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>142.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45</td>\n",
       "      <td>46</td>\n",
       "      <td>大数据时代人工智能在计算机网络技术中的运用</td>\n",
       "      <td>郭磊</td>\n",
       "      <td>科技风</td>\n",
       "      <td>2021-03-10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>252.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>46</td>\n",
       "      <td>47</td>\n",
       "      <td>基于大数据和人工智能的新型医药物流体系构建</td>\n",
       "      <td>陈心媛; 廖吉林</td>\n",
       "      <td>物流科技</td>\n",
       "      <td>2021-03-10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>217.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>47</td>\n",
       "      <td>48</td>\n",
       "      <td>基于人工智能的大数据信息快速抽取算法研究</td>\n",
       "      <td>于晓翠; 陈亮; 林泽源</td>\n",
       "      <td>电子设计工程</td>\n",
       "      <td>2021-03-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>48</td>\n",
       "      <td>49</td>\n",
       "      <td>大数据、AI人工智能对财会从业人员的影响分析</td>\n",
       "      <td>刘红转</td>\n",
       "      <td>商业文化</td>\n",
       "      <td>2021-03-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>49</td>\n",
       "      <td>50</td>\n",
       "      <td>大数据时代人工智能在计算机网络技术中的应用</td>\n",
       "      <td>王晓雨</td>\n",
       "      <td>数字通信世界</td>\n",
       "      <td>2021-03-01</td>\n",
       "      <td>1.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>下载</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0                                                 篇名  \\\n",
       "0            1                      基于大数据和人工智能技术的智库媒体转型——以南方都市报为例   \n",
       "1            2                                 厂商运用大数据和人工智能的经济学分析   \n",
       "2            3                                    人工智能和大数据中的伦理与隐私   \n",
       "3            4                           大数据背景下地方高校人工智能方向人才培养模式探索   \n",
       "4            5                                人工智能及大数据的网络安全态势感知研究   \n",
       "5            6                              大数据、人工智能和实体经济深度融合运用探析   \n",
       "6            7                                大数据+人工智能 构建教育大数据新产业   \n",
       "7            8                            大数据时代人工智能在计算机网络技术中的应用研究   \n",
       "8            9                            基于大数据时代人工智能在计算机网络技术中的应用   \n",
       "9           10                              大数据时代人工智能技术在农业领域的研究进展   \n",
       "10          11                                大数据时代人工智能与学前教育的融合路径   \n",
       "11          12                    大数据与人工智能环境下“一主三辅”情报研究工作模式  网络首发   \n",
       "12          13  后疫情时代教育创新发展的新视域与中国卓越探索——出席“2020全球人工智能与教育大数据大会”的思考   \n",
       "13          14                           大数据时代下人工智能在计算机网络技术中的运用探讨   \n",
       "14          15                              大数据时代背景下人工智能在侦查中的应用思考   \n",
       "15          16                                 关于大数据技术在人工智能中应用的探讨   \n",
       "16          17                              大数据背景下人工智能在智慧交通中的应用研究   \n",
       "17          18                         大数据时代背景下人工智能在计算机网络技术中的应用探索   \n",
       "18          19                              大数据时代人工智能在计算机网络技术中的应用   \n",
       "19          20                                 大数据与人工智能技术助力社区应急管理   \n",
       "20          21                                 人工智能和大数据对会计学科发展的影响   \n",
       "21          22                                    大数据时代人工智能审计模式研究   \n",
       "22          23              人工智能在会计管理中的应用——评《大数据背景下智能会计信息系统构建与应用》   \n",
       "23          24                              大数据下人工智能计算机网络技术中的发展探究   \n",
       "24          25                                       大数据在人工智能中的应用   \n",
       "25          26                              大数据和人工智能在新闻传播生产模式中的应用   \n",
       "26          27                    数学地球科学跨越发展的十年：大数据、人工智能算法正在改变地质学   \n",
       "27          28                           疫情下大数据与人工智能技术在教育领域的应用与思考   \n",
       "28          29                            基于“人工智能+大数据”智慧校园整体规划和建设   \n",
       "29          30                                大数据网络安全防御中人工智能技术的运用   \n",
       "30          31                              物联网大数据人工智能时代引领物业管理新思潮   \n",
       "31          32                            大数据时代人工智能在计算机网络技术中的应用研究   \n",
       "32          33                              大数据时代人工智能在计算机网络技术中的应用   \n",
       "33          34                           大数据背景下人工智能在计算机网络技术中的应用研究   \n",
       "34          35                                      大数据技术在人工智能的运用   \n",
       "35          36                          基于大数据应用和人工智能决策的电网辅助控制体系探讨   \n",
       "36          37                             基于人工智能的网络舆情大数据传播特征挖掘系统   \n",
       "37          38                  一种人工智能精细识别城市用地的方法探索——基于建筑形态与业态大数据   \n",
       "38          39                              大数据与人工智能时代电子发票的内部控制研究   \n",
       "39          40                              大数据时代人工智能在计算机网络技术中的应用   \n",
       "40          41                                 大数据+人工智能推动市域治理模式变革   \n",
       "41          42                              人工智能与大数据在食品安全信息监管中的应用   \n",
       "42          43                                      大数据与人工智能创新实验室   \n",
       "43          44                              基于大数据和人工智能进行网络舆情分析的研究   \n",
       "44          45                    大数据/人工智能背景下IT专业基于R的概率论与数理统计教学改革   \n",
       "45          46                              大数据时代人工智能在计算机网络技术中的运用   \n",
       "46          47                              基于大数据和人工智能的新型医药物流体系构建   \n",
       "47          48                               基于人工智能的大数据信息快速抽取算法研究   \n",
       "48          49                             大数据、AI人工智能对财会从业人员的影响分析   \n",
       "49          50                              大数据时代人工智能在计算机网络技术中的应用   \n",
       "\n",
       "                      作者                 刊名              发表时间   被引     下载  操作  \n",
       "0                    郭全中              新闻与写作        2021-06-05  NaN    NaN  下载  \n",
       "1                    何大安  上海师范大学学报(哲学社会科学版)        2021-05-25  NaN  249.0  下载  \n",
       "2                     丁磊               电子技术        2021-05-20  NaN  618.0  下载  \n",
       "3                叶青; 刘长华           湖北工程学院学报        2021-05-20  NaN   18.0  下载  \n",
       "4          王晓娜; 李晓宇; 李芙蓉          网络安全技术与应用        2021-05-15  NaN  373.0  下载  \n",
       "5                    孟宪坤     中小企业管理与科技(中旬刊)        2021-05-15  NaN  170.0  下载  \n",
       "6                    田雪松            软件和集成电路        2021-05-15  NaN   85.0  下载  \n",
       "7                     郁陶               电子世界        2021-05-15  NaN   65.0  下载  \n",
       "8                    李晓霞               电子测试        2021-05-15  NaN    NaN  下载  \n",
       "9                    朱志锋                新农业        2021-05-10  NaN  221.0  下载  \n",
       "10                   高文慧        中阿科技论坛(中英文)        2021-05-10  NaN   36.0  下载  \n",
       "11                   梁春华            情报理论与实践  2021-05-08 11:00  NaN  187.0  下载  \n",
       "12          陈丽; 任萍萍; 张文梅             中国电化教育        2021-05-08  NaN  961.0  下载  \n",
       "13                   杨文学            电脑知识与技术        2021-05-05  NaN    NaN  下载  \n",
       "14           何明; 李丽; 任红春          电子技术与软件工程        2021-05-01  NaN   49.0  下载  \n",
       "15                    王瑛         现代工业经济和信息化        2021-04-30  NaN  138.0  下载  \n",
       "16                   王洪斌            电脑知识与技术        2021-04-25  NaN  658.0  下载  \n",
       "17                   戚引松              科技与创新        2021-04-25  NaN  371.0  下载  \n",
       "18                   李殿涛               内江科技        2021-04-25  NaN  533.0  下载  \n",
       "19         王惠明; 黄焯威; 付一多             中国物业管理        2021-04-15  NaN   89.0  下载  \n",
       "20                   丁金川                 纳税        2021-04-15  NaN   95.0  下载  \n",
       "21                   杨亦颖                新会计        2021-04-15  NaN   73.0  下载  \n",
       "22                    王巍             中国科技论文        2021-04-15  NaN   11.0  下载  \n",
       "23              郭福燕; 黄稳稳          网络安全技术与应用        2021-04-12  NaN  350.0  下载  \n",
       "24                   龚方生             计算机与网络        2021-04-12  NaN   47.0  下载  \n",
       "25                   姜晓斐               传媒论坛        2021-04-08  NaN  252.0  下载  \n",
       "26     周永章;左仁广;刘刚;袁峰;毛先成         矿物岩石地球化学通报  2021-04-07 11:49  NaN  344.0  下载  \n",
       "27               王桂平; 张涵              计算机时代        2021-04-07  NaN  597.0  下载  \n",
       "28         任新华; 王文冀; 张学燕            电脑知识与技术        2021-04-05  NaN   77.0  下载  \n",
       "29               张超; 郑茗泽              中国新通信        2021-04-05  NaN   24.0  下载  \n",
       "30                    陶青             中国中小企业        2021-04-01  NaN   97.0  下载  \n",
       "31                   雷学智             信息记录材料        2021-04-01  NaN    8.0  下载  \n",
       "32              杨彦青; 郭献崇                科技风        2021-03-29  NaN  597.0  下载  \n",
       "33                段冬; 张娴            电脑知识与技术        2021-03-25  NaN  101.0  下载  \n",
       "34                    李斌          智能建筑与智慧城市        2021-03-25  NaN  339.0  下载  \n",
       "35               蔡新雷; 齐颖               电工技术        2021-03-25  NaN   16.0  下载  \n",
       "36                   洪晓艺               电子技术        2021-03-20  NaN   66.0  下载  \n",
       "37      杨俊宴; 邵典; 王桥; 张宇豪               城市规划  2021-03-15 17:20  NaN  321.0  下载  \n",
       "38                    王佳                 纳税        2021-03-15  NaN  175.0  下载  \n",
       "39                   韩玲玲               电子世界        2021-03-15  NaN  144.0  下载  \n",
       "40                    郑宇                 法人        2021-03-15  NaN   52.0  下载  \n",
       "41  张成梅; 王雅洁; 陶衡; 郝淼; 杨鑫          电子技术与软件工程        2021-03-15  NaN   58.0  下载  \n",
       "42                   NaN      太原学院学报(自然科学版)        2021-03-15  NaN   26.0  下载  \n",
       "43       郭乐江; 肖蕾; 何松; 胡俊             长江信息通信        2021-03-15  NaN  118.0  下载  \n",
       "44                汪浩; 李莹              计算机教育        2021-03-10  NaN  142.0  下载  \n",
       "45                    郭磊                科技风        2021-03-10  NaN  252.0  下载  \n",
       "46              陈心媛; 廖吉林               物流科技        2021-03-10  NaN  217.0  下载  \n",
       "47          于晓翠; 陈亮; 林泽源             电子设计工程        2021-03-05  NaN   38.0  下载  \n",
       "48                   刘红转               商业文化        2021-03-05  NaN   20.0  下载  \n",
       "49                   王晓雨             数字通信世界        2021-03-01  1.0   49.0  下载  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "element=driver.find_element_by_id('gridTable')\n",
    "页面_表格_html=element.get_attribute('innerHTML')\n",
    "pd.read_html(页面_表格_html)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 批量下载"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "driver.find_element_by_xpath('//*[@id=\"divGroup\"]/dl[2]/dd[1]/div/ul[1]/li[2]/input').click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "driver.find_element_by_xpath('/html/body/div[2]/div/div[2]/div/div[1]/div[1]/div[2]/div[2]/input').click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "driver.find_element_by_xpath('//*[@id=\"divGroup\"]/dl[2]/dd[1]/div/ul[1]/li[1]/input').click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "driver.find_element_by_xpath('//*[@id=\"divGroup\"]/div/a[2]').click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# qingchu= (\"//*[@id=\"divGroup\"]/div/a[2]\")\n",
    "# queding=(\"//*[@id=\"divGroup\"]/div/a[1]\")\n",
    "# //*[@id=\"divGroup\"]/dl[1]/dd[1]/div/ul[1]/li[1]/input\n",
    "# //*[@id=\"selectCheckAll1\"]\n",
    "# //*[@id=\"btn-download-all\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "driver.find_element_by_xpath('//*[@id=\"divGroup\"]/dl[2]/dd[1]/div/ul[1]/li[2]/input').click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "driver.find_element_by_xpath('//*[@id=\"divGroup\"]/div/a[1]').click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "driver.find_element_by_xpath('//*[@id=\"divGroup\"]/dl[1]/dd[1]/div/ul[1]/li[1]/input').click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "driver.find_element_by_xpath('//*[@id=\"selectCheckAll1\"]').click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "element=driver.find_element_by_xpath('//*[@id=\"batchOpsBox\"]/li[1]/a')\n",
    "element.click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#  refworks 查看与导出"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['CDwindow-E5D62715DB50D077576616163872F857',\n",
       " 'CDwindow-C740F2A5AAA6912822728B3AE692D3C8',\n",
       " 'CDwindow-CB815747E09F07AD4DA060452642ACBA']"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 切换窗口\n",
    "driver.window_handles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: DeprecationWarning: use driver.switch_to.window instead\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "driver.switch_to_window(driver.window_handles[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "element=driver.find_element_by_xpath('//*[@id=\"btn-download-all\"]')\n",
    "element.click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['CDwindow-E5D62715DB50D077576616163872F857',\n",
       " 'CDwindow-C740F2A5AAA6912822728B3AE692D3C8',\n",
       " 'CDwindow-CB815747E09F07AD4DA060452642ACBA']"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "driver.window_handles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: DeprecationWarning: use driver.switch_to.window instead\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "driver.switch_to_window(driver.window_handles[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "element=driver.find_element_by_xpath('//*[@id=\"gridTable\"]/div[1]/div[2]/div[1]/a')\n",
    "element.click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(0,4):\n",
    "    driver.find_element_by_xpath('//*[@id=\"selectCheckAll1\"]').click()\n",
    "    driver.find_element_by_id('PageNext').click()\n",
    "    time.sleep(5)\n",
    "    display(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "from selenium.webdriver.common.action_chains import ActionChains\n",
    "move = driver.find_element_by_xpath('//*[@id=\"batchOpsBox\"]/li[2]/a')\n",
    "#对定位到的元素执行悬停操作\n",
    "ActionChains(driver).move_to_element(move).perform()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "move = driver.find_element_by_xpath('//*[@id=\"batchOpsBox\"]/li[2]/ul/li[1]/a')\n",
    "ActionChains(driver).move_to_element(move).perform()\n",
    "driver.find_element_by_xpath('//*[@id=\"batchOpsBox\"]/li[2]/ul/li[1]/ul/li[8]/a').click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: DeprecationWarning: use driver.switch_to.window instead\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "driver.switch_to_window(driver.window_handles[3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# //*[@id=\"litotxt\"]\n",
    "# CNKI-20210616012516614.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导出 refworks\n",
    "element=driver.find_element_by_xpath('//*[@id=\"litotxt\"]')\n",
    "element.click()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 李天梅;司小胜;刘翔;裴洪;\\n',\n",
       " 'AD 火箭军工程大学导弹工程学院;\\n',\n",
       " 'T1 大数据下数模联动的随机退化设备剩余寿命预测技术\\n',\n",
       " 'JF 自动化学报\\n',\n",
       " 'OP 1-23\\n',\n",
       " 'K1 大数据;剩余寿命预测;数模联动;深度学习;随机退化建模\\n',\n",
       " ' Big data;remaining useful life prediction;data-model interaction;deep learning;stochastic degradation modeling\\n',\n",
       " '\\n',\n",
       " 'AB 本文面向大数据背景下随机退化设备剩余寿命预测的现实需求,结合随机退化设备监测大数据特点及剩余寿命预测不确定性量化这一核心问题,深入分析了机理模型与数据混合驱动的剩余寿命预测技术、基于机器学习的剩余寿命预测技术、统计数据驱动的剩余寿命预测技术以及机器学习和统计数据驱动相结合的剩余寿命预测技术的基本研究思想和发展动态,剖析了当前研究存在的局限性和共性难题.针对存在的局限性和共性难题,以多源传感监测大数据下剩余寿命预测问题为例,提出了一种数模联动的大数据下随机退化设备剩余寿命预测解决思路,并通过航空发动机多源监测数据初步验证了该思路的可行性和有效性.最后,借鉴数模联动思路,综合考虑机器学习方法和统计数据驱动方法的优势,紧紧扭住大数据背景下随机退化设备剩余寿命预测不确定性量化问题,提出了大数据背景下深度学习与随机退化建模交互联动、监测大数据与剩余寿命及其预测不确定性映射机制、非理想大数据下的剩余寿命预测等亟待解决的关键科学问题.\\n',\n",
       " 'SN 0254-4156\\n',\n",
       " 'CN 11-2109/TP\\n',\n",
       " 'LA 中文\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 王弥;\\n',\n",
       " 'AD 河南工业职业技术学院;\\n',\n",
       " 'T1 基于大数据与信息技术的拖拉机零部件供应链\\n',\n",
       " 'JF 农机化研究\\n',\n",
       " 'YR 2022\\n',\n",
       " 'IS 04\\n',\n",
       " 'vo 44\\n',\n",
       " 'OP 261-264\\n',\n",
       " 'K1 拖拉机部件;供应链管理;大数据;信息化技术;智能分析\\n',\n",
       " ' tractor parts;supply chain management;big data;information technology;intelligent analysis\\n',\n",
       " '\\n',\n",
       " 'AB 为了提高拖拉机零部件供应链管理的水平,提高零部件的管理效率,在供应链管理研究过程中引入了大数据和信息化技术,并在数据分析和处理时采用遗传算法进行优化,确定合理的供应商数据评价函数,提高供应链管理的智能化水平。以拖拉机零部件的供应链管理为例,对比了采用和不采用大数据信息化技术产品的交付时间,结果发现:采用大数据信息化技术可以明显缩短产品的交付时间,提高供应链的管理效率。\\n',\n",
       " 'SN 1003-188X\\n',\n",
       " 'CN 23-1233/S\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 欧阳剑;周裕浩;\\n',\n",
       " 'AD 上海外国语大学图书馆;上海外国语大学新闻传播学院;广西民族大学管理学院;\\n',\n",
       " 'T1 数据驱动型智库研究理念及建设路径\\n',\n",
       " 'JF 智库理论与实践\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 03\\n',\n",
       " 'vo 6\\n',\n",
       " 'OP 20-27+36\\n',\n",
       " 'K1 数据驱动研究;特色智库;大数据;辅助决策\\n',\n",
       " ' data-driven research;think tank with new characteristic;big data;assisted decision making\\n',\n",
       " '\\n',\n",
       " 'AB [目的 /意义]传统的社会科学研究范式是理论驱动型的研究,随着大数据时代的来临,数据驱动研究成为一种新趋势,数据驱动的研究模式给传统领域的研究带来了新的研究方法与范式。大数据给当今的智库研究带来了挑战,同时也为以数据为驱动的智库研究提供了新的契机,数据驱动型智库建设是加强中国特色新型智库建设的方向之一,本文尝试从数据驱动型智库建设出发,探讨数据驱动型智库形成渊源、理念内涵,并对数据驱动型智库建设路径进行了分析,探索其建设思路。[方法 /过程]本文通过对数据驱动型智库建设的渊源分析,探讨数据驱动型智库研究理念,从智库研究范式、数据建设、智库的组织结构及运行机制等角度对数据驱动型智库建设与智库服务等方面进行分析。[结果/结论]本文提出了转变传统研究范式、建立智库数据中台、健全智库大数据隐私保护体系以及提升智库影响力等建设路径,对我国传统智库建设和服务的转型具有一定的借鉴和参考意义。\\n',\n",
       " 'SN 2096-1634\\n',\n",
       " 'CN 10-1413/N\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 赵家正;李辉;\\n',\n",
       " 'AD 中国人民公安大学公安管理学院;\\n',\n",
       " 'T1 公安机关大数据领导力及其提升策略研究\\n',\n",
       " 'JF 智库理论与实践\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 03\\n',\n",
       " 'vo 6\\n',\n",
       " 'OP 37-44\\n',\n",
       " 'K1 公安机关;大数据;领导力;社会治理;提升策略\\n',\n",
       " ' public security organs;big data;leadership;social governance;promotion strategy\\n',\n",
       " '\\n',\n",
       " 'AB [目的 /意义]随着信息技术时代的到来,数据成为一种关键性的战略资源,数据治理成为国家治理和社会治理的重要内容,已经被广泛、深入地应用到公安工作中。[方法 /过程]了解并利用好数据,增强掌握数据的能力,提高利用数据推进各项工作的水平,已经成为提升我国公安机关领导干部整体能力以及治理水平的基本要求。然而,当前,公安机关领导干部仍然存在数据意识匮乏、数据决策失灵、数据共享阻滞等问题。[结果 /结论]领导干部作为整个队伍的带头人,要站在更高的位置,对于大数据等新技术要更加敏感,所以要通过培育数据意识、加强数据培训、开展数据考核、维护数据安全、开放数据共享、完善数据机制等措施,进一步提升大数据领导力。\\n',\n",
       " 'SN 2096-1634\\n',\n",
       " 'CN 10-1413/N\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 马绪峰;赵鑫磊;宋凯;\\n',\n",
       " 'AD 中国传媒大学;韩国世宗大学;中国传媒大学媒体融合与传播国家重点实验室;\\n',\n",
       " 'T1 刍议基于社交媒体数据的电视节目评价体系\\n',\n",
       " 'JF 中国电视\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 65-71\\n',\n",
       " 'K1 大数据;评价体系;社交媒体\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 伴随着技术的创新与迭代,电视节目跨平台、多终端的立体传播将成为未来的趋势。在多媒体传播环境下,如何实现电视节目传播效益的最大化,并通过科学的评估体系对节目的传播进行优化,成为重要的研究课题。本文试图以电视节目《乘风破浪的姐姐》为例,使用数据挖掘、情感算法等方法抓取社交媒体用户数据,从宏观和微观两种维度进行评析,以期完善以大数据为基础的电视节目评价体系,推动电视行业向更好的方向发展。\\n',\n",
       " 'SN 1002-4751\\n',\n",
       " 'CN 11-2750/J\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 雷婷婷;\\n',\n",
       " 'AD 天津工业职业学院;\\n',\n",
       " 'T1 智慧物流在制造企业供应链建设中的策略研究\\n',\n",
       " 'JF 商展经济\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 11\\n',\n",
       " 'OP 67-69\\n',\n",
       " 'K1 智慧物流;供应链;制造业;大数据;物流\\n',\n",
       " ' smart logistics;supply chain;manufacturing;big data;logistics\\n',\n",
       " '\\n',\n",
       " 'AB 随着物流智能化的发展,现代企业的发展越来越离不开物流信息化、网络技术、计算机、通信技术的使用,智能化加快了物流活动的反应能力和作业效率,在制造企业供应链中应用物流智能化是发展趋势,也是企业服务转型升级的重要部分。本文对当前企业智慧物流的现状、问题进行了分析,结合行业特点提出积极有效的解决方案,对制造企业的发展有一定的借鉴价值和启示意义。\\n',\n",
       " 'SN 2096-6776\\n',\n",
       " 'CN 10-1617/F7\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 陈敏;\\n',\n",
       " 'AD 贵州电子信息职业技术学院;\\n',\n",
       " 'T1 大数据环境下企业财会工作的创新模式探讨\\n',\n",
       " 'JF 中小企业管理与科技(中旬刊)\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 76-77\\n',\n",
       " 'K1 大数据;企业;财会工作;创新\\n',\n",
       " ' big data;enterprise;accounting work;innovation\\n',\n",
       " '\\n',\n",
       " 'AB 大数据的飞速发展提高了企业的业务效率,带来了管理上的便利。特别是在财会工作中,大数据的应用是工作方式方面的创新,不仅提高财会工作质量,还带动企业的经济增速加快。论文着重讨论企业在应用大数据系统的环境下,财会工作中突出的问题,并针对这些问题提出创新性的工作思路,以期提高财会的工作质量,给企业带来经济效益。\\n',\n",
       " 'SN 1673-1069\\n',\n",
       " 'CN 13-1355/F\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 任江波;王汾连;何高文;张昕;邓希光;余红霞;\\n',\n",
       " 'AD 南方海洋科学与工程广东省实验室(广州);自然资源部海底矿产资源重点实验室广州海洋地质调查局;青岛斯八达分析测试有限公司;广西隐伏金属矿产勘查重点实验室桂林理工大学;\\n',\n",
       " 'T1 深海富钴结核微区X射线荧光光谱分析和数据挖掘\\n',\n",
       " 'JF 光谱学与光谱分析\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'vo 41\\n',\n",
       " 'OP 1834-1840\\n',\n",
       " 'K1 微区X射线荧光;面扫描;大数据;元素分布;富钴结核;西太平洋\\n',\n",
       " ' Microscopic X-ray florescence spectrometer;Map scanning;Big data;Element distribution;Co-rich ferromanganese nodules;Western Pacific Ocean\\n',\n",
       " '\\n',\n",
       " 'AB 西太平洋富钴结核是近年来新发现的海底固体矿产资源,富含Mn, Fe, Co, Ni和Cu等多种关键金属元素。富钴结核是一种非均质的地球化学和矿物学集合体,粒径约6 cm的结核在生长过程中记录了数千万年的海洋沉积历史,亟需高分辨率的分析技术揭示古海洋环境信息。采用微区X射线荧光光谱仪(μ-XRF),对C3BC1704富钴结核开展多元素面扫描,获得了原位高分辨率多元素的信号强度数据,评价了μ-XRF技术在富钴结核中的应用质量。元素信号谱峰特征和数据频谱分布结果显示,富钴结核中Mn, Fe, Ti, Co, Ca和Ni等元素信号强度敏感,数据呈现相对较好的正态分布特征,可用于定量或半定量分析;Si, Cu和Al等元素信号较弱,数据呈现左偏的正态分布特征,建议相关数据仅作参考。μ-XRF获得的数据量庞大且彼此独立,本研究将不同元素连接成彼此关联的多维矩阵,实现了数据的位置信息和特征元素之间的数学运算和筛选,了解了金属元素的分布和变化特征,揭示了富钴结核生长过程的环境变化。结果显示,Mn和Fe等元素在生长层中波动剧烈,金属元素在富钴结核中的分布极不均匀,显示出多成因类型的交替微层和7个大的生长周期旋回。C3BC1704富钴结核主体暴露在海水中,金属元素主要来自海水,化学组成指示为典型的水成成因。进一步定量分析结果显示,Mn, Cu和Ni等元素含量从内部向外围呈现同步降低的趋势,Fe, Ti和Co等元素含量则呈现同步升高的趋势,这些特征指示早期偏向于成岩富集环境,晚期则以水成富集为主。富钴结核金属元素的分布和变化特征,清晰呈现了富钴结核的生长结构,揭示了富钴结核生长过程的环境变化,有利于富钴结核的成矿模型的构建。\\n',\n",
       " 'SN 1000-0593\\n',\n",
       " 'CN 11-2200/O4\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 许美娟;\\n',\n",
       " 'AD 常州开放大学;\\n',\n",
       " 'T1 大数据下高职院校档案数字化管理创新策略\\n',\n",
       " 'JF 办公自动化\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 12\\n',\n",
       " 'vo 26\\n',\n",
       " 'OP 53-54\\n',\n",
       " 'K1 大数据;高职院校;档案;数字化管理;创新策略\\n',\n",
       " ' big data;higher vocational colleges;archives;digitalized management;innovative strategies\\n',\n",
       " '\\n',\n",
       " 'AB 大数据时代,互联网技术对各领域都产生着深远的影响,高职院校作为社会的一部分,必然顺应时代发展需要,广泛应用数字技术,来有效提升档案管理水平。基于此,本文从档案数字化管理的意义入手,分析档案数字化管理存在问题,探讨如何在大数据背景下创新档案数字化管理。\\n',\n",
       " 'SN 1007-001X\\n',\n",
       " 'CN 11-3749/TP\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 张白洋;\\n',\n",
       " 'AD 天津大学仁爱学院;\\n',\n",
       " 'T1 基于大数据融合的企业商务智能管理探讨\\n',\n",
       " 'JF 现代商贸工业\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 20\\n',\n",
       " 'vo 42\\n',\n",
       " 'OP 32-33\\n',\n",
       " 'K1 大数据;商务智能;数据融合;信息融合;知识融合\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 在大数据的环境下,商务智能的研究是目前企业创新商务模式的热点话题,我国在基于大数据融合方面对商务智能的研究仍有所欠缺。本文首先阐述了大数据融合的概念构架和企业商务智能的发展进程,其次讨论了基于大数据融合的商务智能的发展契机,并从数据融合、信息融合、知识融合三个层面分析了企业商务智能的优化方向,最后探讨了商务智能现在仍存在的问题,为今后的相关研究提供参考。\\n',\n",
       " 'SN 1672-3198\\n',\n",
       " 'CN 42-1687/T\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 彭雪;\\n',\n",
       " 'AD 西南大学;\\n',\n",
       " 'T1 人工智能路径转变关于逻辑推理的批判性思考\\n',\n",
       " 'JF 现代商贸工业\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 20\\n',\n",
       " 'vo 42\\n',\n",
       " 'OP 81-82\\n',\n",
       " 'K1 人工智能;大数据;逻辑推理;反思\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 随着人工智能的不断发展,人工智能研究路径由传统以思维为导向的逻辑推理路径到以大数据为驱动的机器学习的研究路径的转变。本文以IBM深蓝及沃森与Google阿尔法三代对比为切入口,通过对大数据工程式的累积哲学反思逻辑推理。基于逻辑推理在人工智能发展的历史,结合以处理信息不完全的非单调逻辑推理,力致在传统路径与现代路径保持必要张力,以促进人工智能深入的发展。\\n',\n",
       " 'SN 1672-3198\\n',\n",
       " 'CN 42-1687/T\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 秦冲;赵铁柱;柳毅;\\n',\n",
       " 'AD 广东工业大学计算机学院;东莞理工学院计算机科学与技术学院;\\n',\n",
       " 'T1 个性化推荐算法的研究及发展综述\\n',\n",
       " 'JF 东莞理工学院学报\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 03\\n',\n",
       " 'vo 28\\n',\n",
       " 'OP 51-60\\n',\n",
       " 'K1 推荐算法;电子商务;大数据;协同过滤\\n',\n",
       " ' recommendation algorithm;e-commerce;big data;collaborative filtering\\n',\n",
       " '\\n',\n",
       " 'AB 在\"大数据时代\"的背景下,推荐系统能通过分析提取出用户的历史偏好数据,并结合用户之间的偏好关系以及项目与项目的相似程度,推测出目标用户可能喜欢的物品并将其推荐给用户。在当下电子商务时代,推荐系统已成为一种更为活跃、更现代化的信息过滤方式。笔者对推荐系统的研究现状以及主要研究方向进行了系统研究,分析对比了在当下较为流行的各类推荐算法及各自的局限和问题,包括数据的冷启动问题、稀疏性问题、扩展性问题以及推荐性能不高等。最后,总结了目前的推荐系统存在的尚未解决的问题并提出了相应的解决方案。\\n',\n",
       " 'SN 1009-0312\\n',\n",
       " 'CN 44-1456/T\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 马玉成;周莉;周继辉;杨志兵;\\n',\n",
       " 'AD 青海省市场监督管理局;\\n',\n",
       " 'T1 网络安全规划研究与建设实践\\n',\n",
       " 'JF 网络安全技术与应用\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 18-20\\n',\n",
       " 'K1 信息系统;网络安全;规划;云安全;大数据;安全治理\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 以\"六统一\"暨\"统一规划、统一设计、统一标准、统一建设、统一管理、统一运维\"把原来分散在多部门的业务系统以业务数据应用采集、梳理为导向,以云计算、云存储、云安全等技术手段进行分析汇聚,打通信息孤岛,形成互联互通、数据共享、业务协同、统一高效的\"互联网+\"平台。为此,以系统化方式规划统筹网络安全建设,推进信息系统整合提升。着力于\"统筹风险,精益安全,持续推进,人机共智\"从四个方向进行系统安全能力建设,确定了可实施的中长期信息系统安全建设路径,推进业务系统整合数据共享。\\n',\n",
       " 'SN 1009-6833\\n',\n",
       " 'CN 11-4522/TP\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 罗利;\\n',\n",
       " 'AD 湖南信息职业技术学院;\\n',\n",
       " 'T1 Hadoop集群实现词频统计应用\\n',\n",
       " 'JF 网络安全技术与应用\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 64-65\\n',\n",
       " 'K1 大数据;Hadoop;词频统计\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 近年,海量数据分析、数据处理不断发展,大数据技术的应用已深入各行各业,正影响并改变着我们的生活,词频统计是大数据分析中经常要实现的需求。开源大数据平台Hadoop中的WordCount案例可以实现词频统计,该文简要介绍配置Hadoop开发环境,利用Hadoop集群环境实现在HDFS系统上文档中的单词次数统计功能。\\n',\n",
       " 'SN 1009-6833\\n',\n",
       " 'CN 11-4522/TP\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 郑传德;\\n',\n",
       " 'AD 广州商学院;\\n',\n",
       " 'T1 基于网络云空间的在线学习效果评价\\n',\n",
       " 'JF 黑龙江教育(理论与实践)\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 68-70\\n',\n",
       " 'K1 云空间;大数据;互动;在线学习;效果评价\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 在线教学中,学生学习状态监控是一个难点,为有效掌握学生学习效果,基于超星泛雅平台,以\"高等数学\"下册在线教学为背景,以结果为导向,以综合评价为手段,分析系统评价指标及数据采集方法,选取科学的评价指标,建立学习效果评价指标体系,确定各级指标权重,将师生通过云平台教学产生的学习大数据量化处理后转换成适合学习效果评价的基础数据,对学生学习效果进行综合评价,以综合学习成绩的形式较为公正地体现了学生的学习效果,并为教师在线教学前期发现学生学习异常行为提供信息化测评手段。\\n',\n",
       " 'SN 1002-4107\\n',\n",
       " 'CN 23-1064/G4\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 詹浩勇;冯金丽;\\n',\n",
       " 'AD 广西科技大学经济与管理学院;\\n',\n",
       " 'T1 大数据背景下经管类统计学课程开放循环教学体系构建研究\\n',\n",
       " 'JF 现代商贸工业\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 19\\n',\n",
       " 'vo 42\\n',\n",
       " 'OP 129-131\\n',\n",
       " 'K1 大数据;反馈机制;教学模式;开放循环\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 大数据时代的到来不仅带来了经济管理活动方式的变化,也造成了社会对经管类本科人才能力需求的改变。本文从大数据背景下经管类统计学课程对学生能力培养的重要性着手,深入分析了在大数据时代,经管类统计学课程传统教学体系存在的问题,并以构建教学中及时反馈机制和教学后长效反馈机制搭建课程教学供需双方的沟通桥梁,以教学内容和教学方式的优化改革为抓手,设计适应大数据发展要求的统计学课程开放循环教学体系的构建路径。\\n',\n",
       " 'SN 1672-3198\\n',\n",
       " 'CN 42-1687/T\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 Kushwaha Amit Kumar;Kar Arpan Kumar;Dwivedi Yogesh K.\\n',\n",
       " 'AD Department of Management Studies, Indian Institute of Technology Delhi, New Delhi, India;Emerging Markets Research Centre (EMaRC), School of Management, Swansea University, UK\\n',\n",
       " 'T1 Applications of big data in emerging management disciplines: A literature review using text mining\\n',\n",
       " 'JF International Journal of Information Management Data Insights\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 2\\n',\n",
       " 'vo 1\\n',\n",
       " 'K1 Big data;Artificial intelligence;Data science;Marketing;Operations management;Services management;Finance\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB The importance of data-driven decisions and support is increasing day by day in every management area. The constant access to volume, variety, and veracity of data has made big data an integral part of management studies. New sub-management areas are emerging day by day with the support of big data to drive businesses. This study takes a systematic literature review approach to uncover the emerging management areas supported by big data in contemporary times. For this, we have analyzed the research papers published in the reputed management journals in the last ten years, fir using network analysis followed by natural language processing summarization techniques to find the emerging new management areas which are yet to get much attention. Furthermore, we ran the same exercise in each of these management areas to uncover these areas better. This research will act as a reference for future information systems (IS) scholars who want to perform analysis that is deep-dive in nature on each of these management areas, which in the coming times will get all the due attention to become dedicated research domains in the management area. We finally conclude the study by identifying the scope of future research in each of these management areas, which will be a true value addition for IS researchers.\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 Arfanuzzaman Md.\\n',\n",
       " 'AD Food and Agriculture Organization of the United Nations, House # 37, Road #08, Dhanmondi R/A, Dhaka-1205, Bangladesh\\n',\n",
       " 'T1 Harnessing artificial intelligence and big data for SDGs and prosperous urban future in South Asia\\n',\n",
       " 'JF Environmental and Sustainability Indicators\\n',\n",
       " 'YR 2021\\n',\n",
       " 'vo 11\\n',\n",
       " 'K1 Artificial intelligence;Big data;Climate resilience;Data infrastructure;South Asia;SDG;Technological readiness;Urban transformation\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB Artificial intelligence (AI) and big data solutions are currently being utilized to offer low cost and efficient solutions in solving pressing urban socio-economic and environmental problems globally. The study found big data and AI have the potentiality to solve the common urban problems in South Asia and upsurge the efficiency of urban industries, increase competitiveness and productivity of the human and natural resources, reduce the cost of urban service delivery, and build climate resilience. The study has assessed the current AI and big data initiatives and technologies in mitigating the urban development challenges and their potentiality for scaling up in South Asian cities. The study also examined the latest innovations in AI and big data solutions for SDG monitoring and implementation in South Asia and their implication for transformational change. The study suggested that South Asia can harness the maximum benefit of AI and big data technologies by building big data and associated IT infrastructure, advancing research and innovations with regional cooperation, enhancing technological readiness, and eliminating week enabling conditions.\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 Javadian Sabet Alireza;Brambilla Marco;Hosseini Marjan\\n',\n",
       " 'AD Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Via Giuseppe Ponzio, 34/5, I-20133 Milano, Italy;University of Connecticut, Computer Science and Engineering Department, 369 Fairfield Way, Storrs, CT 06268, United States of America\\n',\n",
       " 'T1 A multi-perspective approach for analyzing long-running live events on social media. A case study on the “Big Four” international fashion weeks\\n',\n",
       " 'JF Online Social Networks and Media\\n',\n",
       " 'YR 2021\\n',\n",
       " 'vo 24\\n',\n",
       " 'K1 Digital ecosystems;Long-running live event;Popularity prediction;Fashion week;Big data;Social media;Brand analysis;User generated content;Instagram;Feature selection\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB In the last few years, thanks to the emergence of Web 2.0, social media has made the concept of  online live events  possible. Users participate more and more in  long-running  recurring events in social media by sharing their experiences and desires. In the last few years, thanks to the emergence of Web 2.0, social media has made the concept of  online live events  possible. Users participate more and more in  long-running  recurring events in social media by sharing their experiences and desires. This work introduces long-running live events (LRLEs), as a type of activity that span physical spaces and digital ecosystems, including social media. LRLEs encompass several individuals, organizations, and brands collaborating/competing in the same event. This provides unprecedented opportunities to understand the dynamics and behavior of event-oriented participation, through collection and analysis of data of user behaviors enabled by the Web platform, where most of the digital traces are left by users. What makes this setting interesting is that the behaviors that are traced are not focused only on one individual brand or organization, and thus allows one to understand and compare the respective roles and influence in a defined setting. In this paper we provide a high-level and multi-perspective roadmap to mine, model, and study LRLEs. Among the various aspects, we develop a multi-modal approach to solve the problem of post popularity prediction that exploits potentially influential factors within LRLE. We employ two methods for implementing feature selection, together with an automated grid search for optimizing hyper-parameters in various regression methods.\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 Nagy Enikő;Lovas Róbert;Pintye István;Hajnal Ákos;Kacsuk Péter\\n',\n",
       " 'AD Institute for Computer Science and Control (SZTAKI), Eötvös Loránd Research Network (ELKH), Budapest, Hungary\\n',\n",
       " 'T1 Cloud-agnostic architectures for machine learning based on Apache Spark\\n',\n",
       " 'JF Advances in Engineering Software\\n',\n",
       " 'YR 2021\\n',\n",
       " 'vo 159\\n',\n",
       " 'K1 Reference architectures;Big data;Artificial intelligence;Machine learning;Cloud computing;Orchestration;Distributed computing;Stream processing;Spark\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB Reference architectures for Big Data, machine learning and stream processing include not only recommended practices and interconnected building blocks but considerations for scalability, availability, manageability, and security as well. However, the automated deployment of multi-VM platforms on various clouds leveraging on such reference architectures may raise several issues. The paper focuses particularly on the widespread Apache Spark Big Data platform as the baseline and the Occopus cloud-agnostic orchestrator tool. The set of new generation reference architectures are configurable by human-readable descriptors according to available resources and cloud-providers, and offers various components such as Jupyter Notebook, RStudio, HDFS, and Kafka. These pre-configured reference architectures can be automatically deployed even by the data scientist on-demand, using a multi-cloud approach for a wide range of cloud systems like Amazon AWS, Microsoft Azure, OpenStack, OpenNebula, CloudSigma, etc. Occopus enables the scaling of cluster-oriented components (such as Spark) of the instantiated reference architectures. The presented solution was successfully used in the Hungarian Comparative Agendas Project (CAP) by the Institute for Political Science to classify newspaper articles.\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 Lehrer Steven;Xie Tian;Zhang Xinyu\\n',\n",
       " \"AD Queen's University and NBER, Canada;Shanghai University of Finance and Economics, College of Business, China;Academy of Mathematics and Systems Science, Chinese Academy of Sciences, China\\n\",\n",
       " 'T1 Social media sentiment, model uncertainty, and volatility forecasting\\n',\n",
       " 'JF Economic Modelling\\n',\n",
       " 'YR 2021\\n',\n",
       " 'vo 102\\n',\n",
       " 'K1 Model averaging;Volatility forecasting;Social media;Big data;Sentiment analysis;C52;C53;G12;G17\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB Many economic indicators including consumer confidence indices used to forecast volatility or macroeconomic outcomes, are published with a considerable time lag. To obtain a timelier measure of consumer sentiment many central bank and economic researchers are turning towards using state-of-the-art text sentiment analysis tools. We examine if there are benefits for forecasting volatility from (i) incorporating a sentiment measure derived using deep learning from Twitter messages at the 1-min level, and (ii) acknowledging specification uncertainty of the lag index in the heterogeneous autoregression (HAR) model. We present evidence from an out of sample forecasting exercise that suggests including social media sentiment can significantly improve the forecasting accuracy of a popular volatility index, particularly in short time horizons. Further, our results document large gains in predictive accuracy from a newly proposed estimator that allows for model uncertainty in the specification of the lag index when using a HAR estimator.\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 Santoni Victor;Rufat Samuel\\n',\n",
       " 'AD CY Cergy-Paris University, MRTE, Cergy-Pontoise, France;Institut Universitaire de France, 1 rue Descartes, 75231 Paris, France;33 Boulevard du Port 95000 Cergy France\\n',\n",
       " 'T1 How fast is fast enough? Twitter usability during emergencies\\n',\n",
       " 'JF Geoforum\\n',\n",
       " 'YR 2021\\n',\n",
       " 'vo 124\\n',\n",
       " 'K1 Social media;Emergency management;iVGI;Big data;Attacks;Early warning;Disasters\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB Social media have sparked increasing appeal for improving emergency management. Many have advocated the use of Social Media for Emergency Management (SMEM) to disseminate early warnings. Resorting to the massive but unstructured inVoluntary Geographic Information (iVGI) from social media during disaster response phase has been encouraged for rapid assessment, location and mapping of people and events, for monitoring the expressed needs and for observing human behavior in crisis dynamics. SMEM encompasses top-down – public information, community engagement – bottom-up – situational awareness, urgent needs collection – and many-to-many information flows – allowing a large number of users to communicate with each other simultaneously in real-time. However, operationalizing social media data in real-time during emergency situations might not be as practical as ex post facto retrospective analyses usually suggest. We question the use of SMEM and the unchallenged expectations that they allow for a faster and more widespread dissemination of early warnings, more citizens involvement and offer a richer and more contextualized crowdsourced feedback than classic emergency channels. We analyze the usefulness of geotagged information to monitor the unfolding of a crisis in real time and to accurately detect events and map people. We also question if the use of social media for emergency management is conditioned by local context and governance, by making a comparison between European countries. We offer a critical review of the literature, an SMEM analytical framework, and then empirical work based on large Twitter datasets collected from three different terror attacks in Europe: the Paris attacks in November 2015, the Brussels attacks in March 2016, and the Nice attack in July 2016. The results reveal important delays in warnings and information sharing, and that the press overshadows official accounts. Moreover, first-hand information is often too scattered, too thinly geotagged, and too late to be reliably used during emergency situations.\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 王迎;\\n',\n",
       " 'AD 渭南师范学院人文学院;\\n',\n",
       " 'T1 基于大数据的韩城市典型古民居保护现状调研\\n',\n",
       " 'JF 房地产世界\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 11\\n',\n",
       " 'OP 1-3\\n',\n",
       " 'K1 大数据;韩城古民居;保护;调研\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 韩城市古民居建筑数量众多,其中党家村和韩城古城最具代表性,研究韩城古民居保护发展的意义重大。近年来,韩城市采取了许多措施加大古民居的保护力度,但仍存在使用中的古民居保护力度不够、一些闲置古民居损毁严重、部分古民居因资金等问题拆毁变卖等现象。基于此,应该从提高旅游行业整体服务水平、加强基础设施建设、提高宣传保护力度等方面采取措施,从而更好地保护这些历史遗产。\\n',\n",
       " 'SN 1005-1783\\n',\n",
       " 'CN 36-1182/F\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 陈伟;\\n',\n",
       " 'AD 浙江工商大学人文与传播学院;\\n',\n",
       " 'T1 定量分析：大数据背景下语言哲学研究方法论\\n',\n",
       " 'JF 浙江社会科学\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 110-116+160\\n',\n",
       " 'K1 定量分析;大数据;语言哲学;方法论;语料库\\n',\n",
       " ' quantitative analysis;big data;linguistic philosophy;methodology;corpus\\n',\n",
       " '\\n',\n",
       " 'AB 大数据时代,在数据驱动下人文社会科学的研究方法在某些领域已发生改变,由定性研究为主转向定量研究为主,以语言作为研究对象的语言哲学也是如此。定量分析法之所以越来越受到重视,是因为它能够适应大数据和云计算的需求,可以提高精度以及保证处理结果的准确性和可靠性。语言哲学中定量分析法主要有基于模型技术(计算机模拟、数学模型)的方法,和数据驱动(实验哲学、语料库)的方法,这些方法使得语言哲学的研究对象发生转变,而且为人文社科研究提供新范式,并可对相关研究实践进行重构。大数据时代背景下,数据已成为比自然语言更加精准、便利、可操作、可计算的科学语言,语言哲学研究也将由此发生数据化的变革。\\n',\n",
       " 'SN 1004-2253\\n',\n",
       " 'CN 33-1149/C\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 程晏萍;黄千芷;董慈蔚;\\n',\n",
       " 'AD 华中师范大学图书馆;中南财经政法大学工商管理学院;\\n',\n",
       " 'T1 大数据在供应链管理中应用的研究现状——基于CiteSpace的知识图谱分析\\n',\n",
       " 'JF 华中师范大学学报(自然科学版)\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 03\\n',\n",
       " 'vo 55\\n',\n",
       " 'OP 453-461\\n',\n",
       " 'K1 大数据;供应链管理;Web of Science;知识图谱\\n',\n",
       " ' big data;supply chain management;Web of Science;knowledge map\\n',\n",
       " '\\n',\n",
       " 'AB 为探究大数据在供应链管理中应用的研究现状,文章以Web of Science数据库2012年-2019年收录的151篇相关文献为研究对象,借助CiteSpace软件对收集的文献进行共引网络和关键词共现网络分析,并构建知识图谱,探究该领域的发展趋势、研究概况和当前研究热点.研究表明:1)大数据在供应链管理中应用的研究在发文期刊、国家/地区等方面呈现集中与分散并举的发展状态,其中中国、美国、英国在该领域的研究相对领先于其他国家,且各国之间有较多的合作关系.2)近几年大数据在供应链管理中应用的研究热点主要集中在供应链预测分析、绩效及框架等方面,以模型、物流、数据等为知识基础,是一门涉及多学科领域的研究.3)大数据在供应链管理中的应用,近几年仍处于不断发展的状态,在人才培养、社会应用、风险管理等方面还有较大的研究空间.\\n',\n",
       " 'SN 1000-1190\\n',\n",
       " 'CN 42-1178/N\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 李松波;\\n',\n",
       " 'AD 辽宁师范大学地理科学学院;\\n',\n",
       " 'T1 大数据时代下地理学研究动向与应用前景\\n',\n",
       " 'JF 科技风\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 16\\n',\n",
       " 'OP 71-72\\n',\n",
       " 'K1 地理学;大数据;应用前景\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 大数据时代的来临,引领了地理学的变革与创新。本文对大数据自身特点下,地理学者搜集、提取与利用数据模式的转变,新研究范式产生,宏观、微观研究尺度的结合进行阐述,举例说明不同类型时空大数据对各学科的研究动向。认为挖掘\"科研数据\"新价值,转变科研思维,利用全方位、高精度的大数据确立新型区域规划管理模式,建立校—政—企的信息共享平台等成为今后大数据于地理学的发展趋势。\\n',\n",
       " 'SN 1671-7341\\n',\n",
       " 'CN 13-1322/N\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 张通喜;\\n',\n",
       " 'AD 中国国际航空股份有限公司;\\n',\n",
       " 'T1 大数据在民航飞行训练中的应用\\n',\n",
       " 'JF 科技风\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 16\\n',\n",
       " 'OP 103-104\\n',\n",
       " 'K1 大数据;民航飞行训练;具体应用\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 信息时代下,互联网与社会生产生活的各个领域高度融合,大数据的行业应用受到的关注度日渐提升,并且在各个行业领域中发挥着重要作用。在民航飞行训练中,大数据的应用为训练单位的管理工作和训练方式注入了新的活力,对飞行训练工作的有效性提升起着助推作用,使得经济效益增加的同时,民航飞行训练计划更加完善,也确保了飞行训练的安全性。\\n',\n",
       " 'SN 1671-7341\\n',\n",
       " 'CN 13-1322/N\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 曲畅;\\n',\n",
       " 'AD 长春建筑学院;\\n',\n",
       " 'T1 浅谈大数据在图书馆管理与服务中的应用\\n',\n",
       " 'JF 文化产业\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 16\\n',\n",
       " 'OP 104-105\\n',\n",
       " 'K1 图书馆;服务引擎;管理和服务;大数据融合;管理与服务;图书馆管理人员;大数据;\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 在大数据技术深入人心且广泛应用视域下,大数据时代已然来临,在大数据时代背景下,诸多行业和企业面临着全新的生存和发展压力。同时,也正在依托大数据的优势和影响推动着各项变革,由此可见,各行各业与大数据的融合是一种必然趋势,图书馆也不例外。文章所探究的对象是图书馆,进一步分析和阐述大数据在图书馆管理与服务中的应用,从而找到图书馆管理与大数据融合的契机,为图书馆长远发展奠定坚实的基础。\\n',\n",
       " 'SN 1674-3520\\n',\n",
       " 'CN 14-1347/G2\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 高杰;\\n',\n",
       " 'AD 河南新乡市图书馆;\\n',\n",
       " 'T1 大数据在图书管理中的运用实践\\n',\n",
       " 'JF 发明与创新(职业教育)\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 07\\n',\n",
       " 'OP 245-246\\n',\n",
       " 'K1 大数据;图书馆;图书馆里;技术运用;有效策略\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 在我国信息技术高速发展的背景下,以计算机技术和互联网技术为依托的多种信息技术都在各个行业和领域有了广泛的应用。\"大数据\"是近些年来社会中的热点话题,其在多个行业多有着不同程度的应用。大数据能够与图书管理工作充分的结合,在图书馆中有着深入且广泛的应用,是现代图书馆发展中必然要运用的信息技术。本文对大数据在图书馆管理中的运用进行了深入的研究与分析,并提出了一些合理的运用策略,旨在进一步提高我国图书馆图书管理工作的效率与质量。\\n',\n",
       " 'SN 1672-0954\\n',\n",
       " 'CN 43-1401/N\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 姜圣华;\\n',\n",
       " 'AD 上海市位育中学;\\n',\n",
       " 'T1 高中数学课堂中大数据处理的实践研究\\n',\n",
       " 'JF 现代教学\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 11\\n',\n",
       " 'OP 65-66\\n',\n",
       " 'K1 数学建模;数学课堂;大数据\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 本文通过对一堂数学建模课部分环节的回顾,展示了利用信息技术和\"互联网+\"路径对数学课堂上大数据的处理,并通过实践,总结数学教学中大数据处理的意义及引发的思考。\\n',\n",
       " 'SN 1673-8349\\n',\n",
       " 'CN 31-1991/G4\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 邢会强;\\n',\n",
       " 'AD 中央财经大学法学院;\\n',\n",
       " 'T1 政府数据开放的法律责任与救济机制\\n',\n",
       " 'JF 行政法学研究\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 04\\n',\n",
       " 'OP 41-54\\n',\n",
       " 'K1 开放政府;开放数据;政府数据开放;政府信息公开;大数据\\n',\n",
       " ' Open Government;Open Data;Government Data Opening;Government Information Opening;Big Data\\n',\n",
       " '\\n',\n",
       " 'AB 政府数据开放行为不同于传统的行政行为,它的责任机制是独特的,救济机制也是独特的。政府数据开放并不赋予相对人以主观公权利,至多保障相对人的发展权。政府数据开放法多属于促进型立法,它并不规定政府违反数据开放义务的法律责任。民众较难通过诉权来纠正不予开放相关政府数据的行为,只能借助内部投诉渠道、行政复议或民主参与程序进行纠正。政府开放数据造成数据使用人损害的,政府也不承担责任。政府对不予开放数据的行为导致的纯粹经济损失,更不负赔偿责任。\\n',\n",
       " 'SN 1005-0078\\n',\n",
       " 'CN 11-3110/D\\n',\n",
       " 'LA 中文\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 马会端;\\n',\n",
       " 'AD 东北大学马克思主义学院;\\n',\n",
       " 'T1 大数据系统推介下的网络消费异化：表征、溯因及消解\\n',\n",
       " 'JF 河南师范大学学报(哲学社会科学版)\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 03\\n',\n",
       " 'vo 48\\n',\n",
       " 'OP 41-47\\n',\n",
       " 'K1 大数据;网络消费;消费异化;消费行为;自由异化\\n',\n",
       " ' big data;internet consumption;consumption alienation;consumption behavior;alienation of freedom\\n',\n",
       " '\\n',\n",
       " 'AB 大数据推介系统促进了网络消费的便捷性、多样性以及普遍性。消费异化、网络消费异化、大数据推介系统以及网络消费行为自由异化之间具有内在的逻辑关联。网络消费异化是消费异化的特殊表现形式,而大数据推介系统则构成了网络消费中消费行为自由异化的技术诱因。人们的消费需求、消费心理、消费对象、消费环境异化等是导致网络消费异化问题的基本因素,而这些因素又共同构成了人们进行消费选择的前提条件,并由此导致了网络消费选择中符号化、同质化、被动化等消费行为自由异化的现象。网络消费作为满足人的消费需求的一种手段,基于现实需求的自由消费行为在大数据系统推介下产生了自由的异化,或者说成了一种受大数据推介技术所宰制的异化了的消费自由。在本质上,这种异化了的消费自由是一种消极的消费自由。因此,要在技术开发与实践过程中确立道德责任,促进技术应用者内在德性的养成,让消费者的消费行为建立在自决的判断和选择基础之上。\\n',\n",
       " 'SN 1000-2359\\n',\n",
       " 'CN 41-1011/C\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 朱建军;宋迎春;胡俊;邹滨;吴立新;\\n',\n",
       " 'AD 中南大学地球科学与信息物理学院;\\n',\n",
       " 'T1 测绘大数据时代数据处理理论面临的挑战与发展\\n',\n",
       " 'JF 武汉大学学报(信息科学版)\\n',\n",
       " 'OP 1-8\\n',\n",
       " 'K1 智能测绘;大数据;人工智能;数据处理理论;挑战;发展\\n',\n",
       " ' intelligent surveying and mapping;big data;artificial intelligence;data processing theory;challenges;development\\n',\n",
       " '\\n',\n",
       " 'AB 随着信息技术的发展、测绘大数据和人工智能的兴起，数据缺乏不再是一个问题。可是，现有的测绘数据处理技术一直追求数据的准确性（微观），而大数据研究则恰恰允许数据的混杂性、不确定性（宏观）。因此，尽管传统测绘数据处理理论在微观数据处理方面积累了大量的技术优势，而大数据的规模性和复杂性使得传统的计算模型和分析算法无法有效地支撑大数据的高效分析处理。作为开启智能时代“大门钥匙”的数据处理理论与方法，如何适应新技术的挑战与机遇是值得深入思考的问题。在大数据驱动下，大规模的数据挖掘、机器学习和深度学习等新思想和新方法正在蓬勃发展，极大地促进了场景内外多源异质大数据的融合，从而有效地从多种传感器数据中提取地表特征信息，不断提升测绘信息获取和分析能力。因此，测绘数据处理理论也需要同步跟进，现有的数据处理方法也需要进行智能化。结合智能测绘的前沿热点、发展趋势和存在的挑战，探索数据处理理论扩展的方向，一是希望能够推动测绘数据处理理论的进一步发展，二是希望为有兴趣研究测绘大数据领域的研究生提供学习参考。\\n',\n",
       " 'SN 1671-8860\\n',\n",
       " 'CN 42-1676/TN\\n',\n",
       " 'LA 中文\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 易成岐;窦悦;陈东;郭明军;王建冬;\\n',\n",
       " 'AD 国家信息中心大数据发展部;北京大学信息管理系;中国人民大学信息资源管理学院;\\n',\n",
       " 'T1 全国一体化大数据中心协同创新体系：总体框架与战略价值\\n',\n",
       " 'JF 电子政务\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 2-10\\n',\n",
       " 'K1 大数据;一体化;协同创新;数字经济;新型基础设施\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 党中央、国务院高度重视数字经济高质量发展,明确提出推动建设全国一体化的国家大数据中心,加快新型基础设施建设布局。从构建全国一体化大数据中心协同创新体系的政策背景和国内外研究现状出发,深度剖析了制约我国大数据协同创新发展面临的数据中心布局、算力资源结构、数据流通融合、数据应用创新和数据安全防护等五大瓶颈性问题,从\"数网\"\"数枢\"\"数链\"\"数脑\"\"数盾\"五个方面解析了全国一体化大数据中心协同创新体系总体框架,基于\"聚焦一条主线、把握两大定位、实现三个一体化\"视角,阐述了全国一体化大数据中心协同创新体系的战略价值,以期对促进新型基础设施高质量发展、深化大数据协同创新提供有益参考。\\n',\n",
       " 'SN 1672-7223\\n',\n",
       " 'CN 11-5181/TP\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 王璟璇;窦悦;黄倩倩;童楠楠;\\n',\n",
       " 'AD 国家信息中心大数据发展部;北京大学信息管理系;中国人民大学信息资源管理学院;\\n',\n",
       " 'T1 全国一体化大数据中心引领下超大规模数据要素市场的体系架构与推进路径\\n',\n",
       " 'JF 电子政务\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 20-28\\n',\n",
       " 'K1 数据要素;数据要素市场;大数据;一体化;大数据中心;数据交易\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 党中央、国务院高度重视数据要素市场的培育。随着全国一体化大数据中心建设的推进,我国构建超大规模数据要素市场的先天优势逐步具备。梳理了国内外数据要素市场发展现状及我国数据要素市场发展存在的不充分不平衡等问题,分析了原始数据、脱敏数据、模型化数据、人工智能化数据等四种层次的数据要素形态特征,将全社会范围内数据要素的流动路径划分为数据共享、数据开放、数据交易三类,构建了包括技术层、数据层、政策层等的数据要素体系架构,探讨了全国一体化大数据中心具体支撑数据要素市场培育的四条技术路径,最后从加快数据资源化、资产化、资本化、全球化以及强化数据立法和监管等五个方面提出了配套政策建议。\\n',\n",
       " 'SN 1672-7223\\n',\n",
       " 'CN 11-5181/TP\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 李小庆;\\n',\n",
       " 'AD 中国农业发展银行;\\n',\n",
       " 'T1 基于“大数据+AI”构建全程智能风控体系\\n',\n",
       " 'JF 金融科技时代\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 25-29\\n',\n",
       " 'K1 大数据;人工智能;风险管理;智能风控;云平台\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 受新冠疫情的影响,经济下行压力加大,贷款市场报价利率机制基本形成,银行之间的产品服务具有同质化的趋势,金融市场竞争不断加剧,银行面临更多挑战,特别需要在风险管理领域创新方式方法,推动智能风控体系的构建,实现金融科技、风险管理和业务经营的有效融合。本文深入分析了大数据时代银行风险管理的形势和内涵,提出了基于\"大数据+AI\"的智能风控平台架构,明确智能风控模型构建思路,分析其在客户营销准入、欺诈行为识别、信用风险计量、线上贷款审批、客户关联风险监测、贷后风险监测等场景的应用路径,为银行实现全程智能风险管控提供有益借鉴。\\n',\n",
       " 'SN 2095-0799\\n',\n",
       " 'CN 44-1680/N\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 贾忠恩;\\n',\n",
       " 'AD 甘肃省灵台县第一中学;\\n',\n",
       " 'T1 大数据时代如何提升高中生计算机信息技术水平\\n',\n",
       " 'JF 发明与创新(职业教育)\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 08\\n',\n",
       " 'OP 129-130\\n',\n",
       " 'K1 大数据;高中生;计算机;信息技术\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 随着大数据时代的到来,互联网技术在各行各业普遍应用,计算机信息技术的学习和应用在大数据时代至关重要。随着教育改革的不断普及,素质教育占据主要地位。高中时期正是学生培养能力、学习技能的重要时期,因此,有效的提升高中生的计算机信息技术水平是大数据时代高中计算机信息技术课程教学的重要方向。本文首先介绍了大数据时代计算机信息技术教学的重要性,其次探究了大数据时代提升高中生计算机信息技术水平的有效策略。\\n',\n",
       " 'SN 1672-0954\\n',\n",
       " 'CN 43-1401/N\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 Wang Dong;Thunéll Sven;Lindberg Ulrika;Jiang Lili;Trygg Johan;Tysklind Mats;Souihi Nabil\\n',\n",
       " 'AD Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden. Electronic address: mats.tysklind@umu.se.;Department of Computing Science, Umeå University, SE-901 87 Umeå, Sweden.;Vakin, Övägen 37, SE-904 22 Umeå, Sweden.;Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden. Electronic address: nabil.souihi@umu.se.;Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden.\\n',\n",
       " 'T1 A machine learning framework to improve effluent quality control in wastewater treatment plants.\\n',\n",
       " 'JF The Science of the total environment\\n',\n",
       " 'YR 2021\\n',\n",
       " 'vo 784\\n',\n",
       " 'K1 Big data;Effluent quality;Interpretable AI;Process analytics;Wastewater treatment\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " \"AB Due to the intrinsic complexity of wastewater treatment plant (WWTP) processes, it is always challenging to respond promptly and appropriately to the dynamic process conditions in order to ensure the quality of the effluent, especially when operational cost is a major concern. Machine Learning (ML) methods have therefore been used to model WWTP processes in order to avoid various shortcomings of conventional mechanistic models. However, to the best of the authors' knowledge, no ML applications have focused on investigating how operational factors can affect effluent quality. Additionally, the time lags between process steps have always been neglected, making it difficult to explain the relationships between operational factors and effluent quality. Therefore, this paper presents a novel ML-based framework designed to improve effluent quality control in WWTPs by clarifying the relationships between operational variables and effluent parameters. The framework consists of Random Forest (RF) models, Deep Neural Network (DNN) models, Variable Importance Measure (VIM) analyses, and Partial Dependence Plot (PDP) analyses, and uses a novel approach to account for the impact of time lags between processes. Details of the framework are provided along with a demonstration of its practical applicability based on a case study of the Umeå WWTP in Sweden involving a large number of samples (105763) representing the full scale of the plant's operations. Two effluent parameters, Total Suspended Solids in effluent (TSSe) and Phosphate in effluent (PO4e), and thirty-two operational variables are studied. RF models are developed, validated using DNN models as references, and shown to be suitable for VIM and PDP analyses. VIM identifies the variables that most strongly influence TSSe and PO4e, while PDP elucidates their specific effects on TSSe and PO4e. The major findings are: (1) Influent temperature is the most influential variable for both TSSe and PO4e, but it affects them in different ways; (2) PO4e depends strongly on the TSS in aeration basins - higher TSS concentrations in aeration basins generally promote PO4 removal, but excess TSS can have negative effects; (3) In general, the impact of TSS in aeration basins on TSSe and PO4e increases with the distances of the basin from the merging outlet, so more attention should be paid to the TSS concentration in the third or fourth aeration basins than the first and second ones; (4) Returning excessive amounts of sludge through the second return sludge pipe should be avoided because of its adverse impact on TSSe removal. These results could support the development of more advanced control strategies to increase control precision and reduce running costs in the Umeå WWTP and other similarly configured WWTPs. The framework could also be applied to other parameters in WWTPs and industrial processes in general if sufficient high-resolution data are available.\\n\",\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 冯晓;佟泽华;丰佰恒;薛晓娜;石江翰;\\n',\n",
       " 'AD 山东理工大学信息管理研究院;\\n',\n",
       " 'T1 科研大数据变异的机理研究\\n',\n",
       " 'JF 情报理论与实践\\n',\n",
       " 'OP 1-12\\n',\n",
       " 'K1 科研大数据变异;“VM-SRBD”模型;数据进化;演化机理\\n',\n",
       " ' variation of scientific research big data;\"VM-SRBD\" model;data evolution;evolution mechanism\\n',\n",
       " '\\n',\n",
       " 'AB [目的/意义]科研大数据变异作为数据发展的客观现象是数据质量控制的关键问题，探究其内在机理对于促进数据生态良性发展，巩固国家科研数据成果等方面具备十分重要的意义。[方法/过程]文章以遗传变异理论为基础，对科研大数据变异的概念及特性进行了分析，进而构建了“科研大数据变异演化模型”（VM-SRBD），并从阶段分析、核心活动分析、传播应用分析三方面进行了分解，最后以实际案例对科研大数据的变异演化过程进行了具体论述。[结果/结论]研究表明，科研大数据变异是以不可规避性、双向性、可修复性、可溯源性、遗传性为特征，以变异诱发、变异核心过程、变异传播应用为发展阶段，以数据内生及外生因素为诱发原因，以数据恶性变异及良性进化为发展趋势，以可修复恶性变异数据及进化数据再传播为目标的非线性、多路径、可反馈的动态演化过程。\\n',\n",
       " 'SN 1000-7490\\n',\n",
       " 'CN 11-1762/G3\\n',\n",
       " 'LA 中文\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 詹梨苹;赵锐;杨天学;俞阳;\\n',\n",
       " 'AD 西南交通大学地球科学与环境工程学院;中国环境科学研究院固体废物分质利用与污染控制研究室;\\n',\n",
       " 'T1 基于文献计量分析的大数据驱动城市固体废物监管研究进展\\n',\n",
       " 'JF 环境工程技术学报\\n',\n",
       " 'OP 1-13\\n',\n",
       " 'K1 大数据;固体废物;监管;文献计量分析;决策支持\\n',\n",
       " ' big data;solid waste;supervision;bibliometric analysis;decision support\\n',\n",
       " '\\n',\n",
       " 'AB 利用文献计量学方法，对Web of Science核心合集数据库中2010—2020年大数据驱动固体废物监管的研究论文开展综述研究，通过对发文量、发文机构、出版物、关键词等文献指标统计分析，全面了解其研究现状，掌握其发展趋势，洞悉前沿热点，为推进城市固体废物管理信息化和智能化管理提供科学依据。研究发现：在检索时间段内发文数量呈逐年上升趋势，但发表总量相对较少，共计83篇，说明该研究领域属于新兴、前沿性的研究领域；发表载体主要包括期刊论文、会议论文和综述论文3种类型，论文主要在Sustainability、Journal of Cleaner Production和Waste Management等期刊发表，且具有较高的引用频次；既有研究主要考虑数据工程和数据科学2个维度的应用，以实现固体废物全生命周期的节点管控，前者关注数据源获取以记录废物生命周期的流向与流量信息，后者通过对各类大数据进行建模分析，为提升管控效率提供决策支持。\\n',\n",
       " 'SN 1674-991X\\n',\n",
       " 'CN 11-5972/X\\n',\n",
       " 'LA 中文\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 夏科;陈星;张赐;\\n',\n",
       " 'AD 南充市中心医院·川北医学院第二临床医学院;\\n',\n",
       " 'T1 基于医学装备物联网大数据的智能管理研究\\n',\n",
       " 'JF 科技创新与应用\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 16\\n',\n",
       " 'vo 11\\n',\n",
       " 'OP 191-193\\n',\n",
       " 'K1 医学装备;物联网;大数据;智能管理\\n',\n",
       " ' medical equipment;Internet of Things;big data;intelligent management\\n',\n",
       " '\\n',\n",
       " 'AB 医学装备作为教学、科研、治疗等技术的物质基础,在现代医学诊疗服务中占有举足轻重的地位。通过利用物联网、大数据、5G等现代信息技术手段破除传统管理模式的痛点难点,采集医学装备的运作和管理数据,提升医学装备管理,降低运行使用风险,提高设备使用效率和效益。\\n',\n",
       " 'SN 2095-2945\\n',\n",
       " 'CN 23-1581/G3\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 潘显民;刘树锟;\\n',\n",
       " 'AD 湖南女子学院;\\n',\n",
       " 'T1 大数据环境组件模式教学资源库构建关键问题探究\\n',\n",
       " 'JF 电脑与信息技术\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 03\\n',\n",
       " 'vo 29\\n',\n",
       " 'OP 78-80\\n',\n",
       " 'K1 大数据;教学资源;构建\\n',\n",
       " ' PACS;big data teaching resources construction\\n',\n",
       " '\\n',\n",
       " 'AB 随着大数据时代到来,如何构建高校的大数据环境组件模式教学资源库,成为高校教育资源共享首要解决的问题。文章分析了高校教学资源管理及大数据环境组件模式教学资源库建设中存在的主要问题;设计了大数据环境组件模式教学资源库构建的内容和关键问题;通过集成共享,整合优质教学资源,实现优质教学资源的高度共享与利用。\\n',\n",
       " 'SN 1005-1228\\n',\n",
       " 'CN 43-1202/TP\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 朱炯;刘文;王翀;胡增峣;\\n',\n",
       " 'AD 中国食品药品检定研究院;国家药品监督管理局;\\n',\n",
       " 'T1 我国上市后药品抽查检验工作的现状分析\\n',\n",
       " 'JF 药物评价研究\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'vo 44\\n',\n",
       " 'OP 1207-1214\\n',\n",
       " 'K1 上市后药品;抽查检验;质量;风险;大数据\\n',\n",
       " ' post-marketing drugs;sampling and testing;quality;risk;big data\\n',\n",
       " '\\n',\n",
       " 'AB 我国药品上市后质量抽查检验工作是药品监督执法和风险管理的重要技术支撑手段,有效打击了假冒伪劣药品,保护公众用药安全。这项工作的法律依据充分,主要包括国家药品抽检和地方药品抽检,用于评价和监督药品质量。通过药品抽检可以震慑不法分子,警示用药风险,服务产业发展。然而,抽样和检验工作质量尚需进一步加强,地方保护主义时有存在,建议加强新法规的宣贯培训、加强抽检工作管理、加大制售假劣药品的惩戒力度、加强药品质量风险管理并深挖药品抽检\"大数据\"。\\n',\n",
       " 'SN 1674-6376\\n',\n",
       " 'CN 12-1409/R\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 Bouamrane Karim;Matallah Houcine;Belalem Ghalem\\n',\n",
       " 'AD University of Oran 1, Algeria;Faculty of Science, University of Tlemcen, Algeria;Department of Computer Science, University of Oran 1, Algeria\\n',\n",
       " 'T1 Comparative Study Between the MySQL Relational Database and the MongoDB NoSQL Database\\n',\n",
       " 'JF International Journal of Software Science and Computational Intelligence (IJSSCI)\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 3\\n',\n",
       " 'vo 13\\n',\n",
       " 'K1 Big Data;MongoDB;MySQL;NoSQL;Relational;SQL;Workload;YCSB\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB NoSQL databases are new architectures developed to remedy the various weaknesses that have affected relational databases in highly distributed systems such as cloud computing, social networks, electronic commerce. Several companies loyal to traditional relational SQL databases for several decades seek to switch to the new “NoSQL” databases to meet the new requirements related to the change of scale in data volumetry, the load increases, the diversity of types of data handled, and geographic distribution. This paper develops a comparative study in which the authors will evaluate the performance of two databases very widespread in the field: MySQL as a relational database and MongoDB as a NoSQL database. To accomplish this confrontation, this research uses the Yahoo! Cloud Serving Benchmark (YCSB). This contribution is to provide some answers to choose the appropriate database management system for the type of data used and the type of processing performed on that data.\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 Mohan Prakash;Kuppuraj Balasaravanan;Chellai Saravanakumar\\n',\n",
       " \"AD Karpagam College of Engineering, India;M.P.Nachimuthu M.Jaganathan Engineering College, India;St. Joseph's Institute of Technology, India\\n\",\n",
       " 'T1 An Enhanced Security Measure for Multimedia Images Using Hadoop Cluster\\n',\n",
       " 'JF International Journal of Operations Research and Information Systems (IJORIS)\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 3\\n',\n",
       " 'vo 12\\n',\n",
       " 'K1 Big Data;Clustering;HDFS;MapReduce;Multimedia;Security\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB Information are generated over the internet for every second. These information are not fully secured. To increase the security of these information send over the internet there are two methods Cryptography and Steganography are combined to encrypt the data using RSA algorithm as well as to hide the data in multimedia image in Hadoop Cluster. Features of the resultant image such as color are extracted and stored separately in Hadoop cluster to enhance security. Then combining features of the Stenographic image for secret image retrieval, which has been then split into image and secret information. At last, decrypting the secret information, we retrieve the actual information. Application of this system in Hadoop will increase the speed of execution of the process.\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 陈婷;\\n',\n",
       " 'AD 新疆金风科技股份有限公司;新疆农业职业技术学院;\\n',\n",
       " 'T1 大数据背景下财务会计向管理会计转型探讨\\n',\n",
       " 'JF 中国乡镇企业会计\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 154-155\\n',\n",
       " 'K1 大数据;财务会计;管理会计;转型\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 随着信息技术的不断迭代与发展,为提高企业管理效率,大数据技术已经开始应用到企业的各个部门。财务部门作为企业管理的重要部门,其工作的重点已不再是基础核算业务,面对信息技术在财务工作中的广泛应用,财务会计向管理会计转型是适应企业发展的必然要求。那么,企业财务会计与管理会计之间有什么区别,面对信息技术的应用企业如何推动财务会计向管理会计转型?本文首先介绍了财务会计与管理会计的内涵以及两者之间的关系,在此基础上,提出了财务会计向管理会计转型的策略以供参考。\\n',\n",
       " 'SN 1004-8480\\n',\n",
       " 'CN 11-3064/F\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 刘霞;\\n',\n",
       " 'AD 潍坊万华置业发展有限公司;\\n',\n",
       " 'T1 大数据背景下企业税务会计面临的新挑战及对策\\n',\n",
       " 'JF 中国乡镇企业会计\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 169-170\\n',\n",
       " 'K1 大数据;企业税务会计;新挑战;对策\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 当今社会正处于大数据飞速发展的背景下,许多企业面临着不同于以往的挑战,作为企业发展至关重要的一步的税务会计也面临着许多新的挑战。税务会计在企业中负责按照国家税法及其相关规定对企业收入进行合法纳税,是企业能够平稳有序经营的重要环节的负责人,这就需要企业中的税务会计能够准确合法的计算企业税金,在符合法律规定的条件下让企业能够尽可能的少负税,增加企业的利润。本篇文章针对大数据背景下企业税务会计面临的新挑战及对策展开分析,希望起到参考作用。\\n',\n",
       " 'SN 1004-8480\\n',\n",
       " 'CN 11-3064/F\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 江月;\\n',\n",
       " 'AD 江西财经职业学院;\\n',\n",
       " 'T1 大数据背景下会计课程改革的探索\\n',\n",
       " 'JF 中国乡镇企业会计\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 177-178\\n',\n",
       " 'K1 大数据;会计课程;课程体系;课程考核\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 全球经济的发展,大数据、人工智能、互联网、云计算等信息技术颠覆传统会计行业。在全新信息技术的带动下,会计行业已经出现了智能会计、财务云、数字化会计、会计大数据、区块链技术等热门关键词,会计职业发生了重大变革。本文主要结合大数据背景,探索与思考高职院校会计课程存在问题,针对存在的问题提出改革建议。\\n',\n",
       " 'SN 1004-8480\\n',\n",
       " 'CN 11-3064/F\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 叶志锋;陈洁;\\n',\n",
       " 'AD 广西财经学院会计与审计学院;\\n',\n",
       " 'T1 大数据时代《会计学》课程改革的思考\\n',\n",
       " 'JF 中国农业会计\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 5-7\\n',\n",
       " 'K1 会计学;大数据;业务财务一体化\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 本文在回顾相关文献的基础上,指出当前《会计学》课程教学存在的问题:重核算方法轻思维模式;没有抓住会计工作的本质要求;没有紧贴大数据时代背景。基于大数据时代对会计的影响,提出了改进《会计学》课程教学的建议措施:(1)把《会计学》设置为通识课;(2)围绕会计思维模式这一核心设计课程知识体系;(3)按照业务财务一体化设计授课内容与练习题;(4)体现大数据时代对会计的影响与要求。\\n',\n",
       " 'SN 1003-9759\\n',\n",
       " 'CN 11-2907/F\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 邵川;\\n',\n",
       " 'AD 徐州工程学院金融学院;\\n',\n",
       " 'T1 基于社会治理的中国社会信用体系建设研究\\n',\n",
       " 'JF 社会科学动态\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 42-47\\n',\n",
       " 'K1 社会信用体系;社会治理;大数据;市场经济\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 建设社会信用体系是为了满足我国市场经济发展、提升社会治理能力与完善国家治理体系的需要。改革开放以来,围绕发展市场经济与提升社会治理能力,中国社会信用体系建设经历了由经济领域到全社会领域的拓展,由信用评估评级到诚信建设制度化的深化,由遵守法定义务、履行约定义务到社会意识形态的提升,由纠正违约乱象、理顺信用环境到建设社会信用体系、推进诚信制度化的深入推进,初步完成了中国特色的社会信用体系的顶层设计与失信联合惩戒机制的构建,部分城市推出了城市信用的量化评价。然而,还存在社会信用信息大数据的通联渠道不通畅、地方社会信用体系建设准备不充分、社会信用指标体系不明确等显著问题。这需要通过打通跨部门跨领域信用共享渠道、全面推进信用大数据管理、大力发展信用信息产业、完善信用法律法规建设等措施来推进社会信用体系建设。\\n',\n",
       " 'SN 2096-5982\\n',\n",
       " 'CN 42-1889/C\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Book\\n',\n",
       " 'SR 1\\n',\n",
       " 'T1 Vision, Sensing and Analytics: Integrative Approaches\\n',\n",
       " 'A1 Md Atiqur Rahman Ahad;Atsushi Inoue\\n',\n",
       " 'FD 2021-06-07\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Book\\n',\n",
       " 'SR 1\\n',\n",
       " 'T1 The Big Data-Driven Digital Economy: Artificial and Computational Intelligence\\n',\n",
       " 'A1 Abdalmuttaleb M. A. Musleh Al-Sartawi\\n',\n",
       " 'FD 2021-06-07\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Book\\n',\n",
       " 'SR 1\\n',\n",
       " 'T1 Predictive Intelligence für Manager\\n',\n",
       " 'A1 Uwe Seebacher\\n',\n",
       " 'FD 2021-06-07\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Book\\n',\n",
       " 'SR 1\\n',\n",
       " 'T1 Enabling Machine Learning Applications in Data Science\\n',\n",
       " 'A1 Aboul Ella Hassanien;Ashraf Darwish;Sherine M. Abd El-Kader;Dabiah Ahmed Alboaneen\\n',\n",
       " 'FD 2021-06-07\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Book\\n',\n",
       " 'SR 1\\n',\n",
       " 'T1 Computational Intelligence Methods for Super-Resolution in Image Processing Applications\\n',\n",
       " 'A1 Anand Deshpande;Vania V. Estrela;Navid Razmjooy\\n',\n",
       " 'FD 2021-06-07\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Book\\n',\n",
       " 'SR 1\\n',\n",
       " 'T1 Biomedical Informatics\\n',\n",
       " 'A1 Edward H. Shortliffe;James J. Cimino\\n',\n",
       " 'FD 2021-06-07\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Book\\n',\n",
       " 'SR 1\\n',\n",
       " 'T1 Intelligent Systems in Big Data, Semantic Web and Machine Learning\\n',\n",
       " 'A1 Noreddine Gherabi;Janusz Kacprzyk\\n',\n",
       " 'FD 2021-06-07\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Book\\n',\n",
       " 'SR 1\\n',\n",
       " 'T1 The Palgrave Handbook of FinTech and Blockchain\\n',\n",
       " 'A1 Maurizio Pompella;Roman Matousek\\n',\n",
       " 'FD 2021-06-07\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Book\\n',\n",
       " 'SR 1\\n',\n",
       " 'T1 Essential Tools for Water Resources Analysis, Planning, and Management\\n',\n",
       " 'A1 Omid Bozorg-Haddad\\n',\n",
       " 'FD 2021-06-07\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Book\\n',\n",
       " 'SR 1\\n',\n",
       " 'T1 2020 International Conference on Data Processing Techniques and Applications for Cyber-Physical Systems\\n',\n",
       " 'A1 Chuanchao Huang;Yu-Wei Chan;Neil Yen\\n',\n",
       " 'FD 2021-06-07\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 李玏;廖娟;康艳;\\n',\n",
       " 'AD 四川广播电视大学;\\n',\n",
       " 'T1 大数据背景下高校内部审计信息化构建的探究\\n',\n",
       " 'JF 经济师\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 107-108\\n',\n",
       " 'K1 大数据;高校内部审计;信息化;对策建议\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 随着我国科学技术的飞速发展,大数据时代已然到来。在如今的时代背景下,互联网等信息技术为各行各业带来了巨大的冲击,人们的生活方式也发生了转变。与此同时,各大高校的内部审计部门工作环境发生了巨变。文章对高校内部审计部门信息化建设中存在的相关问题进行研究,提出相应创新和变革的对策。\\n',\n",
       " 'SN 1004-4914\\n',\n",
       " 'CN 14-1069/F\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 马军杰;史轲;\\n',\n",
       " 'AD 同济大学法学院;\\n',\n",
       " 'T1 面向2035年促进科技型中小企业发展的创新栖息地营造\\n',\n",
       " 'JF 中国科技论坛\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 14-17\\n',\n",
       " 'K1 栖息地;大数据;创新生态系统;科技型中小企业;\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB <正>1面向2035的科技型中小企业创新栖息地——创新生态系统的城市模式以知识生产、扩散和传播为目标的创新空间,作为基于知识的城市发展战略,实现了知识密集型网络的空间集聚,并构成城市与区域经济发展的重要引擎与全球知识经济增长的纽带。创新活动一方面加速了城市经济的增长,另一方面促进了城市更新与城市空间质量提升。相应地,城市空间一方面吸引和承接创新资源集聚,另一方面为创新生态系统提供健康生长的栖息地。可见,创新栖息地的营造,\\n',\n",
       " 'SN 1002-6711\\n',\n",
       " 'CN 11-1344/G3\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 李华玮;张沪寅;彭红梅;黄建忠;王毅;关钢;\\n',\n",
       " 'AD 武汉大学计算机学院;\\n',\n",
       " 'T1 “新工科”背景下计算机实践类竞赛案例设计\\n',\n",
       " 'JF 计算机教育\\n',\n",
       " 'YR 2021\\n',\n",
       " 'IS 06\\n',\n",
       " 'OP 32-35+41\\n',\n",
       " 'K1 新工科;实践教学;学科竞赛;大数据;人工智能\\n',\n",
       " ' \\n',\n",
       " '\\n',\n",
       " 'AB 根据\"新工科\"建设理念,结合计算机类专业人才培养的目标,把学科竞赛纳入到教学环节,构建教学、实践、竞赛一体化教学体系,通过两个具体竞赛案例详细阐述计算机实践类竞赛案例的设计过程,最后总结实施效果,对\"新工科\"背景下计算机类专业竞赛案例设计具有一定的参考价值。\\n',\n",
       " 'SN 1672-5913\\n',\n",
       " 'CN 11-5006/TP\\n',\n",
       " 'LA 中文;\\n',\n",
       " 'DS CNKI\\n',\n",
       " '\\n',\n",
       " 'RT Journal Article\\n',\n",
       " 'SR 1\\n',\n",
       " 'A1 万年红;王雪蓉;\\n',\n",
       " ...]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 查看txt\n",
    "with open('CNKI-20210616012516614.txt', encoding='utf-8') as f:\n",
    "    display(f.readlines())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "### 翻页\n",
    "for i in range(0,11):        \n",
    "    if driver.find_element_by_id('changeVercode'):\n",
    "        img_url=driver.find_element_by_id('changeVercode').get_attribute('src')\n",
    "        vercode=identify(img_url)\n",
    "        driver.find_element_by_id('Vercode').send_keys(vercode)\n",
    "        driver.find_element_by_id('checkCodeBtn').click()\n",
    "    else:\n",
    "        driver.find_element_by_id('PageNext').click()\n",
    "        time.sleep(5) \n",
    "## 报错分析：1. Alert Text: 不能超过500个,若要重新选择,请按清除按钮,再进行选取操作，知网只能勾选500个选项，在中国知网检索，一次导出参考文献不能超过500条，分析不能超过200条。对于保存参考文献每次都累加，总数不能超过1500条。进行如下操作，在检索结果列表中勾选参考文献，页面右下角出现一个对话框，如图1，点击“查看已选文献”，跳转到“文献管理中心”页面，如图2，勾选文献，做“全部清除”处理，\n",
    "## 2. 遇到验证码问题，通过使用baidu api ocr 识别，\n",
    "## 3. 延长睡眠时间，保证网络通畅"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ocr 调用api"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'refresh_token': '25.2e5bd6c87e52c705060d94ebf59bc0bf.315360000.1939139554.282335-24376805', 'expires_in': 2592000, 'session_key': '9mzdCS/Zy0sScFvaA1PElSZKPYyWMNb60dImmqIPAXT8voKu6wwuFizBN/FxjIuXEBevFf+sWYS9476VFSG/HBU2U5Yj2w==', 'access_token': '24.2912607a875d6fb494baf8ca997cdc00.2592000.1626371554.282335-24376805', 'scope': 'public vis-ocr_ocr brain_ocr_scope brain_ocr_general brain_ocr_general_basic vis-ocr_business_license brain_ocr_webimage brain_all_scope brain_ocr_idcard brain_ocr_driving_license brain_ocr_vehicle_license vis-ocr_plate_number brain_solution brain_ocr_plate_number brain_ocr_accurate brain_ocr_accurate_basic brain_ocr_receipt brain_ocr_business_license brain_solution_iocr brain_qrcode brain_ocr_handwriting brain_ocr_passport brain_ocr_vat_invoice brain_numbers brain_ocr_business_card brain_ocr_train_ticket brain_ocr_taxi_receipt vis-ocr_household_register vis-ocr_vis-classify_birth_certificate vis-ocr_台湾通行证 vis-ocr_港澳通行证 vis-ocr_机动车购车发票识别 vis-ocr_机动车检验合格证识别 vis-ocr_车辆vin码识别 vis-ocr_定额发票识别 vis-ocr_保单识别 vis-ocr_机打发票识别 vis-ocr_行程单识别 brain_ocr_vin brain_ocr_quota_invoice brain_ocr_birth_certificate brain_ocr_household_register brain_ocr_HK_Macau_pass brain_ocr_taiwan_pass brain_ocr_vehicle_invoice brain_ocr_vehicle_certificate brain_ocr_air_ticket brain_ocr_invoice brain_ocr_insurance_doc brain_formula brain_ocr_facade brain_ocr_meter brain_doc_analysis brain_ocr_webimage_loc brain_ocr_doc_analysis_office brain_vat_invoice_verification wise_adapt lebo_resource_base lightservice_public hetu_basic lightcms_map_poi kaidian_kaidian ApsMisTest_Test权限 vis-classify_flower lpq_开放 cop_helloScope ApsMis_fangdi_permission smartapp_snsapi_base smartapp_mapp_dev_manage iop_autocar oauth_tp_app smartapp_smart_game_openapi oauth_sessionkey smartapp_swanid_verify smartapp_opensource_openapi smartapp_opensource_recapi fake_face_detect_开放Scope vis-ocr_虚拟人物助理 idl-video_虚拟人物助理 smartapp_component smartapp_search_plugin avatar_video_test', 'session_secret': '56c2a7c7f0ad8986a271f90a5c263b8d'}\n"
     ]
    }
   ],
   "source": [
    "## 百度api\n",
    "import requests \n",
    "host = 'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id=ae0r9UouUsjKFGbscXkSlkQY&client_secret=HoLVjtAUCREDrj3mtAflyZxZmN4Ptl4y'\n",
    "response = requests.get(host)\n",
    "if response:\n",
    "    a=response.json()\n",
    "    print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'24.2912607a875d6fb494baf8ca997cdc00.2592000.1626371554.282335-24376805'"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "access_token=a['access_token']\n",
    "access_token"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import base64\n",
    "def identify(img_url):\n",
    "    request_url = \"https://aip.baidubce.com/rest/2.0/ocr/v1/webimage\"\n",
    "    url = img_url\n",
    "    obtain=requests.get(url)\n",
    "    transform=obtain.content\n",
    "    img=base64.b64encode(transform)\n",
    "    params = {\"image\":img}\n",
    "    access_token = '[调用鉴权接口获取的token]'\n",
    "    request_url = request_url + \"?access_token=\" + access_token\n",
    "    headers = {'content-type': 'application/x-www-form-urlencoded'}\n",
    "    response = requests.post(request_url, data=params, headers=headers)\n",
    "    json=response.json()\n",
    "    return(json['xxx']) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
